{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## 强化学习与最优控制：用于轨迹跟踪的 LQR\n",
    "\n",
    "来自知乎：https://zhuanlan.zhihu.com/p/437666628\n",
    "\n",
    "\n",
    "轨迹优化：一辆汽车被赋予一项任务来控制自己，使其遵循定义的航线或轨迹。\n",
    "\n",
    "如果 ᵢ 是时刻 i 的汽车控制 uᵢ= { throttle, Steering }ᵢ\n",
    "\n",
    "汽车需要应用一系列控制操作 U: ₀, ₁, ₂ ... n 以到达所有的点，\n",
    "\n",
    "本文的任务是找到一个可行的控制轨迹 U，使用动态系统 f 生成相应的状态轨迹 X，从而使成本函数 J(U) 最小化。\n",
    "\n",
    "1.控制轨迹 (U)：控制变量 ᵢ 是时刻 i 的输入，序列是这些控制操作（油门、转向），控制操作帮助汽车达到所有目标。\n",
    "\n",
    "\n",
    "2.状态轨迹（X）：状态 ᵢ是对当前场景的描述。 如：汽车的“状态”包括机器人的当前位置（ X、Y 坐标）和方向（yaw γ）。 这种状态受到控制输入变化的影响。\n",
    "\n",
    "![](https://pic3.zhimg.com/80/v2-19d1f51dd3d0ee93399c23bb218c6f6a_1440w.jpg)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3.动态系统（f）：一个数学模型，主要介绍汽车的世界是如何运作的。 当从状态 xᵢ 采取动作 uᵢ 时，模型 f 预测下一个状态 xᵢ+₁。\n",
    "在动力汽车示例中，可以使用运动学方程从数学上确定系统动力学 f\n",
    "\n",
    "4.成本函数（J）：最优控制是关于成本函数的。 它在数学上描述序列问题陈述的目标。 最优控制方法通过优化成本函数 J(U) 来计算最优轨迹 U。\n",
    "\n",
    "\n",
    "\n",
    "![](https://pic1.zhimg.com/80/v2-7219ee6140d34227c275e4172d46f648_1440w.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "在开始定义的轨迹问题中，目标是到达定义的点。 将成本函数定义为汽车位置和下一个点之间的余弦距离，当最小化余弦距离成本时，更接近下一个点。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### LQR\n",
    "\n",
    "\n",
    "最优控制问题的一个特例，即动态方程 f 是线性的，目标函数是 x 和 u 的二次函数。 这个子问题在最优控制中非常重要，因为存在使用微分 Ricatti 方程的 LQR 问题的解析解。 定义系统动力学函数 (f) ，LQR 的成本函数 J(U)，通过在 python 中编写 LQR 来解决汽车轨迹优化问题。\n",
    "\n",
    "![](https://pic4.zhimg.com/80/v2-6b86e8d45831d7d7308bb285d8c34503_1440w.jpg)\n",
    "\n",
    "\n",
    "所以动力学方程是线性的，使用矩阵 A 和 B 来描述线性。 成本函数 J(U) ：它是 x 和 u 的二次函数，\n",
    "\n",
    "![](https://pic4.zhimg.com/80/v2-67c4751f30a5e025574a3a4cb98eaf77_1440w.jpg)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "Q(t) 称为状态成本矩阵。 Q 权衡每个状态在状态向量中的相对重要性。 Q 也可为惩罚机制。 Q 能够通过使 Q 的相应值变大来定位想要低误差的状态。 R(t) 是输入成本矩阵。 该矩阵控制惩罚。\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 代数 Riccati 方程\n",
    "\n",
    "简要讨论 LQR 问题的解析解。 这是有效解的一种简化：控制律可以表示为线性状态反馈\n",
    "\n",
    "![](https://pic1.zhimg.com/80/v2-756e5cf81e653c7075f4fbb29d02b0fc_1440w.png)\n",
    "\n",
    "\n",
    "R 是输入成本矩阵，B 是输入矩阵。 现在 S(t) 是微分 Ricatti 方程的解：\n",
    "\n",
    "![](https://pic1.zhimg.com/80/v2-5908b31a268c4f8a3d2836eab44eb9f0_1440w.png)\n",
    "\n",
    "\n",
    "可以使用反向规约backward induction找到解，直接跳转到最终解：\n",
    "\n",
    "![https://pic2.zhimg.com/80/v2-e6ed411dffa5c2ff4ca6bf2e782c4011_1440w.jpg](https://img-blog.csdnimg.cn/e64a8f9d500042ab94b5410daa6b4239.png)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 轨迹跟踪问题：LQR\n",
    "\n",
    "现在使用 LQR 和 python 实现汽车轨迹跟踪问题。 为了在最优控制范式中定义问题，需要定义状态、控制操作、系统动力学和成本函数。 引入问题本身的同时定义状态向量。\n",
    "\n",
    "![](https://pic3.zhimg.com/80/v2-19d1f51dd3d0ee93399c23bb218c6f6a_1440w.jpg)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "接下来定义线性的系统动力学方程。\n",
    "![](https://pic1.zhimg.com/80/v2-c5e1f7fb8d6b8eea3df5d4255c2facd0_1440w.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "控制操作 uᵢ 包括速度和转向输入。 现在使用无摩擦运动学方程的案例来近似汽车在世界上的运动。\n",
    "\n",
    "![](https://pic3.zhimg.com/80/v2-89f6e8b66a0966fde95624795d73c3de_1440w.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "接下来使用矩阵来查找 A 和 B 矩阵\n",
    "\n",
    "\n",
    "![](https://pic2.zhimg.com/v2-fe2e7a535379f736974d4338466ab591_r.jpg)\n",
    "\n",
    "Q 矩阵为正定矩阵，惩罚希望汽车所处的位置与当前位置之间的差异。 通过使 Q 的相应值变大来定位我们想要低误差的状态。 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt \n",
    "import matplotlib.animation as animation \n",
    "import numpy as np \n",
    "import time\n",
    "np.set_printoptions(precision=3,suppress=True)\n",
    "max_linear_velocity = 3.0\n",
    "max_angular_velocity = 1.5708"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](https://pic2.zhimg.com/v2-fe2e7a535379f736974d4338466ab591_r.jpg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def getB(yaw, deltat):\n",
    "    \"\"\"_summary_\n",
    "    矩阵B\n",
    "    Args:\n",
    "        yaw (_type_): _description_\n",
    "        deltat (_type_): _description_\n",
    "\n",
    "    Returns:\n",
    "        _type_: _description_\n",
    "    \"\"\"\n",
    "    B = np.array([\n",
    "            [np.cos(yaw)*deltat, 0],\n",
    "            [np.sin(yaw)*deltat, 0], \n",
    "            [0, deltat]\n",
    "            ])\n",
    "    return B\n",
    "\n",
    "\n",
    "def state_space_model(A, state_t_minus_1, B, control_input_t_minus_1):\n",
    "    \"\"\"_summary_\n",
    "    状态方程\n",
    "    Args:\n",
    "        A (_type_): _description_\n",
    "        state_t_minus_1 (_type_): _description_\n",
    "        B (_type_): _description_\n",
    "        control_input_t_minus_1 (_type_): _description_\n",
    "\n",
    "    Returns:\n",
    "        _type_: _description_\n",
    "    \"\"\"\n",
    "    state_estimate_t = (A @ state_t_minus_1) + (B @ control_input_t_minus_1)\n",
    "    return state_estimate_t\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5\n",
      "4\n",
      "3\n",
      "2\n",
      "1\n"
     ]
    }
   ],
   "source": [
    "for i in range(5, 0, -1):\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![https://pic2.zhimg.com/80/v2-e6ed411dffa5c2ff4ca6bf2e782c4011_1440w.jpg](https://img-blog.csdnimg.cn/e64a8f9d500042ab94b5410daa6b4239.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def lqr(actual_state_x, desired_state_xf, Q, R, A, B, dt):\n",
    "    x_error = actual_state_x - desired_state_xf\n",
    "    N = 100\n",
    "    P = [None] * (N + 1)\n",
    "    Qf = Q\n",
    "    P[N] = Qf\n",
    "    \"\"\"从最后一步开始\"\"\"\n",
    "    for i in range(N, 0, -1):\n",
    "        \"\"\"计算P矩阵\"\"\"\n",
    "        P[i-1] = Q + A.T @ P[i] @ A - (A.T @ P[i] @ B) @ np.linalg.pinv(\n",
    "            R + B.T @ P[i] @ B) @ (B.T @ P[i] @ A)\n",
    "    K = [None] * N\n",
    "    u = [None] * N\n",
    "    for i in range(N):\n",
    "        \"\"\"计算K和U\"\"\"\n",
    "        K[i] = -np.linalg.pinv(R + B.T @ P[i+1] @ B) @ B.T @ P[i+1] @ A\n",
    "        u[i] = K[i] @ x_error\n",
    "    u_star = u[N-1]\n",
    "    return u_star\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_control_waypoints(waypoints, R, dt=0.5, error_th=1, verbose=False):\n",
    "    waypoints = [np.array(i) for i in waypoints]\n",
    "    trajectory = []\n",
    "    controls = []\n",
    "    error = []\n",
    "    waypoints_reached = []\n",
    "    actual_state_x = np.array([0, 0, 0])  # 初始状态\n",
    "    A = np.array([[1.0,  0,   0], [0, 1.0,   0], [0,  0, 1.0]])  # 矩阵A\n",
    "    Q = np.array([[1, 0, 0], [0, 1.0, 0], [0, 0, 1.0]])  # 矩阵Q\n",
    "    for desired_state_xf in waypoints:\n",
    "        state_error_magnitude = 1e10\n",
    "        waypoints_reached.append(actual_state_x)\n",
    "        while state_error_magnitude >= error_th:\n",
    "            if verbose:\n",
    "                print(f'Current State = {actual_state_x}')\n",
    "                print(f'Desired State = {desired_state_xf}')\n",
    "            state_error = actual_state_x - desired_state_xf\n",
    "            trajectory.append(actual_state_x)\n",
    "            state_error_magnitude = np.linalg.norm(state_error)\n",
    "            error.append(state_error_magnitude)\n",
    "            if verbose:\n",
    "                print(f'State Error Magnitude = {state_error_magnitude}')\n",
    "            \n",
    "            B = getB(actual_state_x[2], dt)\n",
    "            \n",
    "            optimal_control_input = lqr(actual_state_x,desired_state_xf, Q, R, A, B, dt)\n",
    "\n",
    "            \n",
    "            controls.append(optimal_control_input)\n",
    "            if verbose:\n",
    "                print(f'Control Input = {optimal_control_input}')\n",
    "            actual_state_x = state_space_model(A, actual_state_x, B, optimal_control_input)\n",
    "            if verbose:\n",
    "                if state_error_magnitude < error_th:\n",
    "                    print(\"\\nGoal Has Been Reached Successfully!\")\n",
    "    return(trajectory, controls, waypoints_reached, error)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 画图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_animation(waypoints,trajectory,verbose=False,marker_txt=True):\n",
    "    plt.style.use('dark_background')\n",
    "    fig = plt.figure(figsize=(10, 10)) \n",
    "    ax = plt.axes(xlim=(0, 110), ylim=(0, 110)) \n",
    "    y = np.array(waypoints).T[1]\n",
    "    z = np.array(waypoints).T[0]\n",
    "    n = [i for i in range(len(waypoints))]\n",
    "    if marker_txt:\n",
    "        ax.scatter(z, y,color=\"Red\")\n",
    "        for i, txt in enumerate(n):\n",
    "            ax.annotate(txt, (z[i], y[i]),color=\"Red\")\n",
    "    else:\n",
    "        n = [i for i in range(len(waypoints)) if i%20==0]\n",
    "        for i, txt in enumerate(n):\n",
    "            ax.plot(z, y, \"-r\", label=\"course\")\n",
    "            ax.annotate(txt, (z[txt], y[txt]),color=\"Red\") \n",
    "        plt.subplots()\n",
    "        plt.plot(np.array(waypoints).T[0], np.array(waypoints).T[1], \"-r\", label=\"spline\")\n",
    "        plt.plot(np.array(trajectory).T[0], np.array(trajectory).T[1], \"-g\", label=\"tracking\")\n",
    "        plt.axis(\"equal\")\n",
    "        plt.xlabel(\"x[m]\")\n",
    "        plt.ylabel(\"y[m]\")\n",
    "        plt.legend()\n",
    "    line, = ax.plot([], [],lw=2,   marker='>',markersize=6, ) \n",
    "    label = ax.text(40, 100, 'control', fontsize=12, color=\"Red\")\n",
    "    \n",
    "    def init(): \n",
    "        line.set_data([], []) \n",
    "        return line, \n",
    "    xdata, ydata = [], [] \n",
    "    \n",
    "    def animate(i): \n",
    "        x = trajectory[i][0]\n",
    "        y = trajectory[i][1]\n",
    "        xdata.append(x) \n",
    "        ydata.append(y) \n",
    "        line.set_data(xdata, ydata)\n",
    "        text_ = \"       CONTROL\\n\"+'Velocity: '+ str(np.round(controls[i][0],2))+'\\nAngular-velocity: '+str(np.round(controls[i][1],2))\n",
    "        label.set_text(text_)\n",
    "        if verbose:\n",
    "            print(i,x,y)\n",
    "        return line, \n",
    "    anim = animation.FuncAnimation(fig, animate, init_func=init, \n",
    "                                  frames=len(trajectory), interval=1, blit=True,) \n",
    "    anim.save('coil.gif',writer='imagemagick')\n",
    "    plt.subplots()\n",
    "    plt.plot(np.arange(len(controls)), np.array(controls).T[0], \"-r\", label=\"Velocity\")\n",
    "    plt.xlabel(\"Time [s]\")\n",
    "    plt.ylabel(\"Velocity\")\n",
    "    plt.show()\n",
    "    plt.subplots()\n",
    "    plt.plot(np.arange(len(controls)), np.array(controls).T[1], \"-r\", label=\"Angular Velocity\")\n",
    "    plt.xlabel(\"Time [s]\")\n",
    "    plt.ylabel(\"angular Velocity\")\n",
    "    plt.show()\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "MovieWriter imagemagick unavailable; using Pillow instead.\n"
     ]
    },
    {
     "data": {
      "image/png": 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w4QTUksTtOAgaIKhIQC1ubmncmiH44YI/BT/687PBbXN/F9xz18+C1e95V9CcgNo6s0XeYrV+/XqqqsLRF1VVVWzYsAGA1atXc9xxreP7Bw0axOrVq9s9x5QpUxg1ahSjRo1i48aNHSlDUgecTTgmqhi4gXBc1HOxVpRMeYTTNczAweRSR2UvSGnuVUxLURFrR/wNM++8g0e+8VUqMi1Y3U2HgtXs2bOpqakBoKamhkceeSS3/6qrwgudTzvtNLZt25brMpSUDH9L2FW1EbiQcL6o9qZD6Ml6E3YdfhS75qTOuKGdfS3FRbwx9uNc+R/fPur1HA2Fhzrgnnvu4cMf/jD9+/dn5cqVfPOb3+T73/8+M2fO5Oqrr2b58uWMHTsWgF//+tecd955LF26lB07dvCZz3ymy9+ApCPzLVw25VB24FxSUhTuJbwCsK2WXbv4v1mP8uTkaXGU1OUOGawuv3zfqQdDZ511Vrv7v/jFL3auIkmS1K007dpNQXEReXl53Pqp8az9y5K4S+oyzrwuSZK6zOpFi3lu1mz2NIbXH29ase80xd3LIVusJEmSOurWsTUUFBXxd+MupXlPE7t3du9RnbZYSZKkLlVaEa6PsLOu+19ja7CSJEldqiQXrOoPcWT6GawkSVKXKq0Ir7O1xUqSJKmTsl2BjbZYSZIkdU5pZbbFymAlSZLUKbnB69vtCpQkSeqUUgevS5IkRaPEweuSJEnRyA1er2+IuZKuZ7CSJEldyglCJUmSIpKbIHS7Y6wkSZI6JTtBaKMtVpIkSZ3jVYGSJEkRcUkbSZKkiDjGSpIkKQIFhYX06l1Kc1MTu3fujLucLmewkiRJXaakBy3ADAYrSZLUhXrSwHUwWEmSpC7Ukwaug8FKkiR1odauwO6/nA0YrCRJUhfqScvZgMFKkiR1IcdYSZIkRcQxVpIkSREpqbTFSpIkKRI9aQFmMFhJkqQuVNqDlrMBg5UkSepCrWOsDFaSJEmd4nQLkiRJESlxugVJkqRolFZmBq9vt8VKkiSpU0rKywDYWW+LlSRJUoflFxRQUlZGS3Mzu3fsjLuco8JgJUmSukS2taqxvoEgCGKu5ugwWEmSpC7R05azAYOVJEmJdx2wEFgA3AP0irWaw1da2bMmBwWDlSRJiTYQuBZ4H/AeoAAYF2tFh88WK0mSlDiFQClhqOoNrIm3nMPW0+awAoOVJEmJtga4BVgBrAW2AU/EWtHha12AuecEq8K4C5AkSaHrZ07nzfkLOOHU9/LGiy/xxM+mUbBxExcDQ4GtwP3Ap4C74yz0ELLvo37zFqBndQUarCRJSojq4cMYcMIQCnsVU3XCED748Qv4yHd/yOBfzeGju3ZxL/AQ8AGSHayy7yOvIOwYa2lujrmio8dgJUlSF+jVuzclFWWUlJdTWl6eu11SUU5peevtkvIySisqKKkI53wq7FUMQF5BAS0FBbzyiYuonr+QD0yfzHvz8znnOz9g7V8P48ZPXhLjuzu07PsA+NAV4yguLeWJn02jbuOmGKvqegYrSVK3kO1+iuKX9xGFonYCUklZGfkFBZG8r3WnvJslH/0Il18xnpbCQjb89TBeu2IspcXFh35yQhQUFfK3Yz9O1UlD+elnvhB3OV3KYCVJ6hay3U/vv+QCXvrNU7ww61Gam5rCcFRx6FCUPa5XWW8KCjv/63HXjp001tfTWN9AY109jfX17MzdbmBnXV24r64hPK6unn+a9tP9T9TczAufu4q6AW/j1Gm/4NTf/h5O/32n6+tKN/3pydztpt27aWlp4YWHf8mTk6fFWNXRYbCSJHUb2e6nURefx6iLz+vweQ4ZijJBqLE+DEU7t9ftvb+hgZamjo0ratq1O3wfzc0U7Gni3Q8/yujJ0yjbtJk3gcYOv6ujq2nXblqC1kBVt2lz3CUdFQYrSVK3FQQBO7fXsfi52gOHokxwasy0HO2sr+9wKOqs1YsWs2z+y4w8dQTve3EeH8wEKoAG4IZYqjpy2ffRkwJVlsFKktTtBEHAnl27UtdacuvYGgBmAZcBf004MegKwlB1b2yVHZns++iJDFaSpG6jafceCouL2NWwg+9fMDY1gao995KeIKVWzrwuSeoWVi9azEuPh3OS79i2PdWhSulli5UkqVu4dWwNfQdW8b6LOj5oXeosW6wkSZIiYrCSJEmKiMFKkiQpIgYrSZKkiBisJEmSImKwkiRJiojBSpIkKSIGK0mSpIgYrCRJkiJisJIkSYqIwUqSJCkiBitJkqSIGKwkSZIiYrCSJEmKiMFKkiQpIgYrSZKkiBisJEmSImKwkiRJiojBSpIkKSIGK0mSpIgYrCRJkiJisJIkSYqIwUqSJCkiBitJkqSIGKwkSZIiYrCSJEmKiMFKkiQpIgYrSZKkiBisJEmSImKwkiRJiojBSpIkKSIGK0mSpIgYrCRJkiJisJIkSYqIwUqS1C0NA+a12bYBX461IvUEhXEXIElSV1gMjMjczgdWA7PiK0c9hC1WkqRu70zgdWBF3IWo2zNYSZK6vXHAvXEXoR6hU8HquuuuY+HChSxYsIB77rmHXr16MWTIEJ577jmWLFnCjBkzKCoqiqpWSZKOWBFwEXB/3IWoR+hwsBo4cCDXXnst73vf+3jPe95DQUEB48aN4+abb+a2227j5JNPZsuWLVx99dVR1itJUruunzmdz3/xGgAGA8uAy4BzgbnAhvhKUw/SqRarwsJCSktLKSgooHfv3qxdu5YzzjiDBx54AIDp06dzySWXRFGnJEkHVT18GP3POxuAxmMq6d+/H1OAidgNqKOnw8FqzZo13HLLLaxYsYK1a9eybds2XnzxRbZu3UpzczMAq1atorq6OrJiJUk6qIICAPaU9Wbq4w/y/L9cy6i8PB6KuSz1HB0OVn369OHiiy9m6NChDBw4kLKyMs4555zDfv748eOpra2ltraW/v37d7QMSZL2l5dHc69evHTlOGbe9TO2x12PeowOB6uzzjqLZcuWsXHjRpqamnjooYcYM2YMffr0oSDzP4ZBgwaxevXqdp8/ZcoURo0axahRo9i4cWNHy5Ak6aB2EcRdgnqQDgerFStWMHr0aEpLSwE488wzefXVV3nmmWe49NJLAaipqeGRRx6JplJJkg5XEFDQ2Mg773uQZ677etzVqAfp8MzrL7zwAg888ABz586lqamJefPm8fOf/5xf/epXzJgxgxtvvJF58+YxderUKOuVJOmAguZm8goKKGpo4KMX/APf3rTZges6qjq1pM2kSZOYNGnSXvuWLVvGaaed1pnTSpJ0xFYvWszapW/wvgvPYd3WbQzftDnuktQDOfO6JKnbyMsLfwaB46oUDxdhliR1C9XDhzHgxKEAlPXpQ0X/ftRt3BRzVeppbLGSJHUbhcXhMmol5WV847EH+MQ3vkpF/34xV6WexGAlSep28vLyKCop4W/Hfpwr/+PbcZejHsSuQElSt9PS0kLT7t288PAveXLytLjLUQ9isJIkdRtNe5ooLCpk69r1/OenPkedVwbqKLMrUJLULaxetJg3/jwXgGXz5huqFAuDlSSpW7h1bA2v/Pb3AOysq4+5GvVUBitJUrdRUlEBQKPBSjExWEmSuo3S8nLAFivFx2AlSeo2Siuywaou5krUUxmsJEndRkmFLVaKl8FKktRtlFZmx1jZYqV4GKwkSd1Gritwuy1WiofBSpLUbZRmrgp0jJXiYrCSJHUbpY6xUswMVpKkbiM7eN15rBQXg5UkqVsoLi2loLCQXTt20tzUFHc56qEMVpKkbqG0MtNaVW9rleJjsJIkdQslzrquBDBYSZK6hVLXCVQCGKwkSd2Cy9koCQxWkqRuITvGyq5AxclgJUnqFnKTg263xUrxMVhJkroFF2BWEhisJEndQuvgdVusFB+DlSSpW3A5GyWBwUqS1C2UVjrdguJnsJIkdQu2WCkJDFaSpG6hdeZ1x1gpPgYrSVK3YIuVksBgJUnqFkqceV0JYLCSJHULrYPXG2KuRD2ZwUqSlHpFJb0oLCpiT+Mumnbvjrsc9WAGK0lS6uWWs7EbUDEzWEmSUs+B60oKg5UkKfVssVJSGKwkSalXUhm2WDlwXXEzWEmSUq/UyUGVEAYrSVLqlTjGSglhsJIkpV52jFWjLVaKmcFKkpR6pZW2WCkZDFaSpNTLXRW43WCleBmsJEmpV+o6gUoIg5UkKfWcIFRJYbCSJKVeiROEKiEMVpKk1Mu2WDXaYqWYGawkSalXWpltsTJYKV4GK0lS6pWUlwEGK8XPYCVJSrXC4mKKevWiafdumnbtirsc9XAGK0lSqnlFoJLEYCVJSrXc+KrtXhGo+BmsJEmp5gLMShKDlSQp1VyAWUlisJIkpZpjrJQkBitJUqrlFmA2WCkBDFaSpFQrrXTWdSWHwUqSlGol5XYFKjkMVpKkVGsdY+XgdcXPYCVJSjUHrytJDFaSpFQryS3AbIuV4mewkiSlWrbFqnG7LVaKn8FKkpRqrdMt2GKl+BmsJEmp5hgrJYnBSpKUarZYKUkMVpKk1CosLqaopBdNe/awp3FX3OVIBitJUnqVVJQBzrqu5DBYSZJSy1nXlTQGK0lSajm+SkljsJIkpVZuDitbrJQQBitJUmqV5mZdN1gpGQxWkqTUys1htd2uQCWDwUqSlFpODqqkMVhJklKrxMHrShiDlSQptRy8rqQxWEmSUis3eL3eYKVkMFhJklKrpDyceX3ndoOVksFgJUlKrewEoY2OsVJCGKwkSanlVYFKGoOVJCm1XNJGSWOwkiSlVkluglBbrJQMBitJUioVFBbSq3cpzU1N7N65M+5yJMBgJUlKqRLnsFICGawkSankwHUlkcFKkpRKDlxXEhmsJEmpVFqZ7QpsiLkSqZXBSpKUSiXl2a5AW6yUHAYrSVIqOcZKSWSwkiSlkmOslEQGK0lSKpVU2mKl5OlUsDrmmGO4//77WbRoEa+++iqjR4+mb9++zJkzh8WLFzNnzhz69OkTUamSJLVyAWYlUaeC1e23387jjz/O8OHDOeWUU1i0aBETJ07kqaeeYtiwYTz11FNMnDgxqlolScopdTkbJVCHg1VlZSUf+tCHmDp1KgB79uxh27ZtXHzxxUyfPh2A6dOnc8kll0RSqCRJbbWOsTJYKTk6HKyGDh3KW2+9xbRp05g7dy5Tpkyhd+/eDBgwgHXr1gGwbt06BgwYEFmxkiRltV4VaFegkqPDwaqwsJCRI0dyxx13MHLkSBoaGtrt9guCoN3njx8/ntraWmpra+nfv39Hy5Ak9VAlTregBOpwsFq1ahWrVq3ihRdeAOCBBx5g5MiRrF+/nqqqKgCqqqrYsGFDu8+fMmUKo0aNYtSoUWzcuLGjZUiSeqhSF2FWAnU4WK1fv56VK1cybNgwAM4880xeffVVZs+eTU1NDQA1NTU88sgj0VQqSVIbJXYFKoEKO/PkL33pS9x9990UFxfzxhtv8JnPfIb8/HxmzpzJ1VdfzfLlyxk7dmxUtUqSBEB+QQElZWW0NDeze8fOuMuRcjoVrObPn8+oUaP223/WWWd15rSSJB1USXkZAI31DQccyyvFwZnXJUmp43I2SiqDlSQpdUornRxUyWSwkiSlji1WSiqDlSQpdZzDSkllsJIkpU7rAswGKyWLwUqSlDq55WzqDVZKFoOVJCl1sl2BjdsdY6VkMVhJklKn1DFWSiiDlSQpdVqvCjRYKVkMVpKk1Cl1nUAllMFKkpQ6JZV2BSqZDFaSpNTJdQU6eF0JY7CSJKVOtivQeayUNAYrSVLquKSNkspgJUlKlfyCAkrKy2hpaWFXw464y5H2YrCSJKVKr7IyAHbVNxAEQczVSHszWEmSUqW0IgxWXhGoJDJYSZJSxfFVSjKDlSQpVUpczkYJZrCSJKVKtsWq0RYrJZDBSpKUKqXOuq4EM1hJklKlddZ1g5WSx2AlSUoVF2BWkhmsJEmp4uB1JZnBSpKUKg5eV5IZrCRJqdI6QWhDzJVI+zNYSZJSpcQJQpVgBitJUqpkB683OsZKCWSwkiSlikvaKMkMVpKkVCn1qkAlmMFKkpQaeXl59CoPB6831jt4XcljsJIkpUav8jLy8/PZWVdP0NISdznSfgxWkqTUcNZ1JZ3BSpKUGq2Tgzq+SslksJIkpUauxareYKVkMlhJklIju05g43aDlZLJYCVJSo3WOawMVkomg5UkKTUcvK6kM1hJklLDyUGVdAYrSVJqlFS6nI2SzWAlSUqNUgevK+EMVpKk1HABZiWdwUqSlBqOsVLSGawkSalhi5WSzmAlSUqNkooyABrrGmKuRGqfwUqSlBq2WCnpDFaSpFTIy8ujpDzTYlVvi5WSyWAlSUqF4t6l5BcU0NjQQEtzc9zlSO0yWEmSUiHbDdjoFYFKMIOVJCkVSiudakHJZ7CSJKVCbuD6dgeuK7kMVpKkVHByUKWBwUqSlAolTrWgFDBYSZJSIbcAs1MtKMEMVpKkVCjJdQXaYqXkMlhJklIh12K13TFWSi6DlSQpFVzORmlgsJIkpYJXBSoNDFaSpFRobbEyWCm5DFaSpFQoyc687gShSjCDlSQpFewKVBoYrCRJqdC6CLMtVkoug5UkKRVKyssA2Flvi5WSy2AlSUq84tJSCgoL2bVjJy1NzXGXIx2QwUqSlHilmYHrjY6vUsIZrCRJiefkoEoLg5UkKfG8IlBpYbCSJCVeiS1WSgmDlSQp8RxjpbQwWEmSEs/lbJQWBitJUuLlxli5nI0SzmAlSUo8W6yUFgYrSVLitV4VaIuVks1gJUlKvJJMsGqsb4i5EungDFaSpMRzjJXSwmAlSUq8EicIVUoYrCRJieeSNkoLg5UkKfGyXYFOEKqkM1hJkhLP6RaUFgYrSVKiFZeWUFBUyO6djTTv2RN3OdJBGawkSYnmAsxKE4OVJCnRSr0iUClisJIkJVppeXZyUIOVks9gJUlKtJJKW6yUHgYrSVKiZa8IbHTWdaWAwUqSlGiOsVKaGKx0UMcA9wOLgFeB0fGWo4xlwMvAPKA25lqkruYcVkqTwrgLULLdDjwOfBIoAnrHW47a+AiwKe4ipKOgtcXKrkAln8FKB1QJfAj4dOb+HmBbbNVI6qkcvK40sStQe7l+5nQ+8Y2vUtG/H//+g2/T9PYqftGrF3OBKdhidTS0/Qzauw8QAHOAPwPjY6lS6nq5v/v9wr/7Dl5XGnS6xSo/P58///nPrF69mgsvvJAhQ4YwY8YM+vXrx4svvsiVV17JHpcgSI3q4cMYcMIQ3v/xC6ha+gYnbniL56b+mP/aXsdZt/wnP2hq5vbjquMus2Py8uKu4LBUDx9G1ckncNrfX8SbLy3Y6/783zzFH+65nwvf2sjaggL6Nzfz4MbNrOlTyZ969Yq7dClS1cOHMeDEoeQXFoQ78mwLUPJ1Olh9+ctfZtGiRVRWVgJw8803c9ttt3Hfffdxxx13cPXVVzN58uROF6qjp7BXMQB1A95G3YC/4q1T38u7gYLKCs6d+r/s+ukP4y2wBygoDL+aJ40audf9Uy84h1MvOGevY+t++t/8S+9SXvz0p45ukdJRUFhclLt92U3/ygmnnsITP5tG3UZHGCqZOhWsqqurOf/887npppu4/vrrATjjjDO4/PLLAZg+fTqTJk0yWKXUjv79qKsaQN9ly9kydDDHP/9nNp84JO6yerzCHTvJa2lmV2ER9atWM/C3f+CZyz/JplVr4i5NilS/QQP3ul9YXMzfjv04VScN5aef+UJMVUkH16lg9aMf/Yivfe1rVGQuhe3Xrx9bt26lubkZgFWrVlFdndJuIwHwzNev59yJkyjYvZst1W/nO6e+l0c+fD51mzbHXdp+evXuTUlFGaUVFZSUl4e3y8tzt0vKyymtKKekvKz9x8vKyC8o6HQdu3bsoLGugZ319TTW19NY10BjfX14P3O7sb6endszP+sbaKzL3K5r4MY//iZ3rqZdu3MtiAAFu3ZTuWYtf/+P11G0aTOvNzfzc+C7/3Zjp+uWkuaHC/6Uu920azctQQsvPPxLnpw8LcaqpIPrcLA6//zz2bBhA3PnzuX0008/4uePHz+ea665BoD+/ft3tAx1gYJdu8kLWmgqKWHT0CHMnH4H73z4l3xi8jTqnv1jl7xmNhSVlJeHYaeyPNmhKLu/rn6vULSroYGWzH8sOqPtL5G/G3dp7jN518O/ZPTkaZRt2kwL8O5Ov5KUbPsGqiT+p05qq8PBasyYMVx00UWcd955lJSUUFlZye23306fPn0oKCigubmZQYMGsXr16nafP2XKFKZMmQJAba1THMbt+pnTeXP+AiqWvM4JL85j9ORpPHTHbQyc/zKjJ0/jrU2bOdD1OPuFolwQqkh0KAoDUXj8zu31kYWizlq9aDHL5r+c+yVy/il/w5DM51DW5pfKihhrlI6Gfb8LUhrkEV653Smnn346X/3qV7nwwguZOXMmDz74YG7w+ssvv8wdd9xx0OfX1tYyatSozpahTvjhgj/RtGs3+cBxL87jhOfCsLurvJz6ygp+X17Gui4NRTtbW4COMBQ11tXT2NBAS1P8oagrXEY41UVZm30NhNMs3BtLRZLUsx0st0Q+QeiECROYMWMGN954I/PmzWPq1KlRv4S6SHYsz+oPnMbqD5y212P9Mlt7sqGoca+xQoaiqGTD03eB4wlbqm7AUCVJSRRJsHr22Wd59tlnAVi2bBmnnXbaIZ6hNAiCgC1r1vLsXfcaimJ2LwYpSUoDl7TRfoKWFvbs3u1gUUmSjpDBSjlNe/ZQWFREw9Zt3PKJKwxUkiQdIdcHEBBefbPw6d8BsGXdekOVJEkdYLASALeOreG30+4O7wSdvlBUkqQeyWAlSZIUEYOVWuXlAeHVgJIk6cgZrJSTyVWSJKmDDFbanw1WkiR1iMFKrewKlCSpUwxWkiRJETFYKScvO8jKFitJkjrEYKWcPBy9LklSZxistJ/A0euSJHWIwUqtcl2B8ZYhSVJaGawkSZIiYrBSTuvYdZusJEnqCIOVWnlVoCRJnWKwkiRJiojBSjl5zrwuSVKnGKwkSZIiYrBSq2yLlfMtSJLUIQYr5eTmXTdXSZLUIQYrSZKkiBis1MrB65IkdYrBSjnZqwIlSVLHGKy0P1usJEnqEIOVcpzHSpKkzjFYSZIkRcRgpVa5tQLjLUOSpLQyWCmnNVeZrCRJ6giDlSRJUkQMVmoj22Rli5UkSR1hsJIkSYqIwUo5TrcgSVLnGKzUKs+uQEmSOsNgJUmSFBGDlXJssJIkqXMMVpIkSRExWKlVdvC6E4RKktQhBivl5DmPlSRJnWKwkiRJiojBSq2cx0qSpE4xWCknr3UVZkmS1AEGK0mSpIgYrJTTOo+VTVaSJHWEwUqSJCkiBiu1cup1SZI6xWClnDwnCJUkqVMMVpIkSRExWKkNuwIlSeoMg5UkSVJEDFbKcey6JEmdY7BSK5e0kSSpUwxWkiRJETFYKSfPvkBJkjrFYKX92BUoSVLHGKzUKttiJUmSOsRgpZw8g5UkSZ1isJIkSYqIwUo52fYqx1hJktQxBivtz2AlSVKHGKzUyjFWkiR1isFKOXnOvC5JUqcYrCRJkiJisFIrZ16XJKlTDFbKyeWqeMuQJCm1DFaSJEkRMViplV2BkiR1isFK+/GqQEmSOsZgpZw8nMdKkqTOMFiplfNYSZLUKQYrSZKkiBislJPnfAuSJHWKwUr7sStQkqSOMVgpxzWYJUnqHIOVWuWSlS1WkiR1hMFKkiQpIgYr5WTnsXKMlSRJHWOw0v7MVZIkdYjBSq0cvS5JUqcYrJTTugazTVaSJHWEwUr7M1hJktQhBiu1sitQkqROMVgpJ89FmCVJ6hSDlSRJUkQMVmqVbbFyvgVJkjrEYNUFegHPAy8BC4FJcRbTEfvkqnxgLvBoHLVIkpQihXEX0B3tAs4AGgj/gP8APEYYtpIsO/P6vr4MLAIqj2o1kiSljy1WXaQh87Mos6Wic62deayqgfOB/46lIEmS0sVg1UXygXnABuAJ4IV4y+mwHwFfA1pirkOSpDTocLAaNGgQTz/9NK+88goLFy7k2muvBaBv377MmTOHxYsXM2fOHPr06RNVranSAowABgHvB94VbzmHJa916nUgbKnaQDi+SpIkHVqHx1g1NTXxz//8z8ybN4/y8nJefPFFnnjiCT796U/z1FNPcfPNNzNhwgQmTpzIxIkTo6w5Ma6fOZ035y/ghFPfS8GLL1Hzs2m8Y+MmVgA3APcC24BngHOAV+Is9hC+V/sMO7fXAXBSELAMGAw0A5/M/KwE/he4Mq4iJUlKuA4Hq3Xr1rFu3ToA6uvrWbRoEdXV1Vx88cV8+MMfBmD69On89re/7bbBqnr4MAacMITCXsVwwhDmfPwCVv7ycUZNmc5Pt2wlPy+PXwYBH2vcxS1FRfQqLIi75AMqLimhqFcvAAadcxa973+YvMVLKQR6A7cStsAZqiRJOrA8IhhXPXjwYH73u9/x7ne/mxUrVtC3b9/cY1u2bNnrfntqa2sZNWrUEb9utsXoiZ9No27jpiN+PoTdX8W9SyktL6ekopyS8nJKKspy90uz+8rL9rpdUlHOwGEntXvO/n9Zyjn/+m3ymlvICwIWn30Gz/2/qztUXywyXYHHLn2D8yZO4m2Ll7IO+DNwYayFSZIUv4Pllk4Hq7KyMp599lluuukmZs2atV+Q2rx5M8cee+x+zxs/fjzXXHMNAP3792fo0KFH/No/XPAnmnbtJggCFj7zO+b+ag4tLc1hKMoEpJLybDgqo7SiIheKSsrD8NSrvIz8/C4Ywx8E5DW3sLOxMfpzd4GS8rL9dwYBxfX1fPEDZ9MCJLe9TZKko+dgwapT81gVFhby4IMPcvfddzNr1iwA1q9fT1VVFevWraOqqooNGza0+9wpU6YwZcqUXIEdrqFXMQAjzv0oI879aIfOsWvHDhrrGthZX09jfT076+pprKunsb6Bxrr6zP6GzL56dmZu//MDd+1/suZmCvY08e6HH6V68jSGb9rc4fd2NP1wwZ9a72RarPotfZ3zJkwCYEUMNUmSlDadClZTp05l0aJF3Hbbbbl9s2fPpqamhptvvpmamhoeeeSRThd5JIIgoGHLVhY8/SyNdQ00ZsPS9r1DURigGtjV0EBLc3OHX69p1+4w3LUJVKMnT4NNmxkf4fs6GoJcF+DrXDBhEn+15HUgnJPrhhjrkiQpLTocrMaMGcNVV13Fyy+/zLx58wC44YYb+P73v8/MmTO5+uqrWb58OWPHjo2s2EPZ3djICw//kicnT6PuKLQUrV60mGXzX+bEU0dQ8OI8Pj15GsM2bd7rqsC02N3YyMaVq7hnwiQ+vOR1PgL0g1S+F0mS4hLJ4PXO6ujg9ewYq4LiIvLy8rjxnE+wZfXaLqhQkiQpdLDckuqZ11cvWsxzs2azp3EXAPUpGc8kSZK6p1Qvwnzr2BoA3n/xBTFXIkmSlPIWK0mSpCQxWEmSJEXEYCVJkhQRg5UkSVJEDFaSJEkRMVhJkiRFxGAlSZIUEYOVJElSRAxWkiRJETFYSZIkRcRgJUmSFBGDlSRJUkQMVpIkSRExWEmSJEXEYCVJkhQRg5UkSVJEDFaSJEkRMVhJkiRFxGAlSZIUEYOVJElSRAxWkiRJETFYSZIkRcRgJUmSFBGDlSRJUkQMVpIkSRExWEmSJEXEYCVJkhQRg5UkSVJEDFaSJEkRMVhJkiRFxGAlSZIUEYOVJElSRAxWkiRJETFYSZIkRaRbBKuK9Rv45Ge/wPxdu1kIXBt3QZIkqUfqFsGqpaCAZ796Laf0KmY08AVgeNxFSZKkHqcw7gKi0NC/H3uOqwagHlgEVGd+SpIkHS3dosWqrcHACOD5uAuRJEk9TrcKVmVBwIPAdUBdzLVIkqSeJ7VdgZcBZ86czvHzF/AKwJ4m7tuzh7uBWfGWJkmSeqhUtlhdBkwBtg0fxoJPXkJLr2LO/uZNUFrKbXEXJ0mSeqxUBqvvAmXZOwUFDHxpAe989HFGvL2KN972V8wvKODcGOuTJEk9Uyq7Ao/f5/6akadw64I/ARAEAcvnL+SxK685+oVJkqQeLZUtVisOeURwFKqQJEnaWyqD1Q1Aw747g4CWxkb+eN+D3Hnd12OoSpIk9XSp7Aq8N/PzfQDNzVBQQPPORr5z3qXUbdocY2WSJKknS2WLFYThavWixcz7zdMAvLVmraFKkiTFKrXBCuDWsTX8ccYDAOysq4+5GkmS1NOlOlgBlFRUALCzzrnWJUlSvFIfrEorwhmtGm2xkiRJMesGwSrbYmWwkiRJ8Up9sCqpKAcMVpIkKX6pD1bZFqtGx1hJkqSYdYNgZYuVJElKhvQHq8rOj7GaCqwHFkRTkiRJ6qHSH6yyLVbbO94VeCdwTjTlSJKkHiz1waqkvPNdgb8HnLNdkiR1VuqDVesYKwevS5KkeKU+WGWnW3CCUEmSFLfCuAvoqOtnTufN+QuOePD692qfYdPK1WyeOIl/W7yU44EVwK1dV6okSeohUhusqocP4+3DTiS/oICW5mYGvuMk6jdvOeTziktKqDrpBN7+wF08tXwlF/7zNxiyeCnfBzZ1fdmSJKkbS22wAsgvKMj9vO7e/zns5+Xl5QGwbcjx/OKBu7jkn65n8J9qGdTczErgm8Dhn02SJCmU6mAVibw8Hv7prRTX1/NPHzib4+KuR5IkpVa3ClZBELB13Xp+e+c9NNY30Fhfz866ehrr62msC+9/+/ePt30CAP2Wvs55EyaxIqa6JUlS99AtglXQ0sKe3bt54eFf8uTkadRtOvisVEEQkEdroPqrJa/TAHz5qFQrSZK6q1QHq5aWFvLz81n3xpv87HNfOmSgAtjd2MjGlavYPGES/77kdfoBbwI3APd2cb2SJKl7S22wWr1oMTvr6zlp1EiWzZ1/WKEK4OujPpK7Pa2ripMkST1SaicIvXVsDS899mTcZUiSJOWkNlhJkiQlTbcJVh8DXgOWABNirkWSJPVM3SJY5be08BPgXOCdwGXA8HhLkiRJPVC3CFYnrVnLUmAZsAeYAVwcb0mSJKkH6hbB6tjt9axsc38VUB1XMZIkqcfqFsFKkiQpCVI7j9W3Z07n+PoGNgGjKsvp2+axQcDqmOqSJEk9VypbrC4DyoYPY9OppwDw5vkf4135+VwLFAHjgNkx1idJknqmVAar72Zv5Iflbzr5RH5563e56di+/CU/n5nAq3EVJ0mSeqxUdgUev++O/HxeP/N0Xj/jQ7w5fyH/deU1cZQlSZJ6uFS2WK046KPBUapCkiRpb6kMVjfsu6OlhfzGRjbc9yB3Xvf1OEqSJElKZ1fgvcD7AFpaID+ffi++xFP/8m/876bNMVcmSZJ6slQGK4DVixZT3LuUvxp8HLff/zDzDFWSJClmqewKBLh1bA2bVoazVe2sq4u5GkmSpBQHK4CSijIAdtbVx1yJJElSyoNVaUUFADu322IlSZLil/JgVQ7YYiVJkpIh5cEqbLFqrDdYSZKk+KU2WBUWF1NU0oumPXvY07gr7nIkSZK6Jlh97GMf47XXXmPJkiVMmDChK16ideC646skSVJCRD6PVX5+Pj/5yU/46Ec/yqpVq6itrWX27NksWrQoste4fuZ01i9bBkCj46skSVJCRB6s3v/+97N06VKWZYLPjBkzuPjiiw8arPoNquYdH3g/DVu3HdZrVA8fRtXJJwBQUlFORf9+1G3c1PniJUmSOiHyYFVdXc3KlStz91etWsVpp5120OeUHlPBNT+7/Yhep6AwLL2sbx++8dgDvPDwr3jiZ9MMWJIkKTaxLWkzfvx4rrnmGgCOKerF5Se+GwLYtWMHb7254qDPHfSuv95vX80738eu6/7lkM/V4evfvz8bN26Muwy14WeSPH4myeTnkjzd6TMZPHjwQR8PotxGjx4dPP7447n7EydODCZOnHjQ59TW1kZag1s0m59L8jY/k+RtfibJ3Pxckrf1lM8k8qsCa2trOfnkkxkyZAhFRUWMGzeO2bNnR/0ykiRJiRN5V2BzczNf/OIX+c1vfkNBQQH/8z//w6uvvhr1y0iSJCVOl4yxeuyxx3jssccO+/if//znXVGGOsnPJXn8TJLHzySZ/FySp6d8JnmEfYKSJEnqpNQuaSNJkpQ0sQero7H8jQ5u0KBBPP3007zyyissXLiQa6+9FoC+ffsyZ84cFi9ezJw5c+jTp0+8hfZA+fn5zJ07l0cffRSAIUOG8Nxzz7FkyRJmzJhBUVFRzBX2PMcccwz3338/ixYt4tVXX2X06NF+V2J23XXXsXDhQhYsWMA999xDr169/K7EYOrUqaxfv54FCxbk9h3su3H77bezZMkS5s+fz4gRI2KouOvEd0lifn6wdOnSYOjQoUFRUVHw0ksvBcOHD4/9UsmetlVVVQUjRowIgKC8vDz4y1/+EgwfPjy4+eabgwkTJgRAMGHChOD73/9+7LX2tO0rX/lKcPfddwePPvpoAAT33Xdf8A//8A8BENxxxx3B5z//+dhr7GnbnXfeGVx99dUBEBQVFQXHHHOM35UYt4EDBwZvvPFGUFJSEkD4HampqfG7EsP2wQ9+MBgxYkSwYMGC3L4DfTfOPffc4Ne//nUABKeddlrw3HPPxV5/hFt8L96ROa/cun57+OGHg7POOit47bXXgqqqqgDC8PXaa6/FXltP2qqrq4Mnn3wy+MhHPpILVm+99VZQUFAQwP7fH7eu3yorK4M33nhjv/1+V+LbBg4cGKxYsSLo27dvUFBQEDz66KPB2Wef7Xclpm3w4MF7BasDfTcmT54cjBs3rt3j0r7F2hXY3vI31dXVMVakwYMHM2LECJ5//nkGDBjAunXrAFi3bh0DBgyIubqe5Uc/+hFf+9rXaGlpAaBfv35s3bqV5uZmwO9LHIYOHcpbb73FtGnTmDt3LlOmTKF3795+V2K0Zs0abrnlFlasWMHatWvZtm0bL774ot+VhDjQd6M7//6PfYyVkqOsrIwHH3yQ6667jrq6uv0eD4Ighqp6pvPPP58NGzYwd+7cuEtRG4WFhYwcOZI77riDkSNH0tDQwMSJE/c7zu/K0dOnTx8uvvhihg4dysCBAykrK+Occ86JuywdQE/4bsQarFavXs1xxx2Xuz9o0CBWr14dY0U9V2FhIQ8++CB33303s2bNAmD9+vVUVVUBUFVVxYYNG+IssUcZM2YMF110EcuWLWPGjBmcccYZ3H777fTp04eCggLA70scVq1axapVq3jhhRcAeOCBBxg5cqTflRidddZZLFu2jI0bN9LU1MRDDz3EmDFj/K4kxIG+G93593+swcrlb5Jj6tSpLFq0iNtuuy23b/bs2dTU1ABQU1PDI488Eld5Pc4NN9zAcccdx9ChQxk3bhxPP/00V1xxBc888wyXXnop4GcSh/Xr17Ny5UqGDRsGwJlnnsmrr77qdyVGK1asYPTo0ZSWlgKtn4nflWQ40Hdj9uzZXHXVVQCcdtppbNu2Lddl2B3EOsjr3HPPDf7yl78ES5cuDW644YbYB531xG3MmDFBEATB/Pnzg3nz5gXz5s0Lzj333ODYY48NnnzyyWDx4sXBE088EfTt2zf2Wnvidvrpp+cGrw8dOjR4/vnngyVLlgQzZ84MiouLY6+vp22nnHJKUFtbG8yfPz+YNWtW0KdPH78rMW+TJk0KFi1aFCxYsCC46667guLiYr8rMWz33HNPsGbNmmD37t3BypUrg89+9rMH/W78+Mc/DpYuXRq8/PLLwamnnhp7/VFtzrwuSZIUEQevS5IkRcRgJUmSFBGDlSRJUkQMVpIkSRExWEmSJEXEYCVJkhQRg5UkSVJEDFaSJEkR+f8xqIcUysqbBQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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zJywF4Pzzzz/ms9raWl+MyUV9fT3V1dVUV1ezbZvTuq01BxG13zhkfLedUxCfws9tKwiED/pmjqTgtt8I4jd6zA5eBQCilc/yCsANN9zAsmXL+OpXv0pzc/OR49NPP2XZsmVB2ug7UYzNucHNJDCTOPnASysI4uEHu6QQq6G2uzg3qf4C9yEgiJa/8vYBPP3008ybN4/f/va33HbbbUc+b29v58svvwzEuKDYAPxz2EZIwEsLYAOdG1fb2Uc3qrgZ026SPSBgpRxzIo/XViNEq0DzmxQif+xycW4U/ZW3BWAYBuvXr+fGG2+kvb39yAHQv39/KTd/+umnee+99xg5ciQtLS1MmTJFynWdEofwRxlihILXzKy6H2QUaKr7wAle/GWep/1ljz2ICWFR8lfBFsDFF1/M4sWLMQzjqOUgDMNgxIgRnm/+/e9/3/M1ZNAC9ERMCHOygFiU8BLLhaNrJ+HNyvBOCviry3M3AYeIVg3Nb1LAApfnHkBsd5gkf7mdA2AStVBrXgG4+OKLARg+fHhgxoRFdmxOVQHwEpuEaDZPneK1FXQI0X+gsg+cYG6d6aVAi8voMbukgGYP50fNX5ajgC655BL69u0cF1FaWsqkSZN8NSpo4lD4eRWAzUR342q7ePUBxCMcaJdyhAhof9nDy6xpk6i1ACwFYPr06ezcufPI3zt27GD69Om+GhU0cYj9phAFeJvL86O8cbVdZAlAlDKon3gNG0Ky/OVl1rRJC6KlGpW5E5YC0K3bsV8pLracQKwUWxDxTJUTcgrYiCjI3aJ6ZpYhABtIzrh2Wf4yR4/FHVn+gujkM0sBWLRoEffffz/Dhw9n+PDh3H///SxevDgI2wLDQLzUqLwUN3gZnWAStfikU7y2gkCIYAlihmvckdViArXTjV3i6C9LAfjJT37CgQMHeO6553juuefYv38/N954YxC2BYrqsUwZAhDVjavtIqsVBGqnBbukEGvUb/dwjaT5C+QIQFT8ZRnL2bNnDz//+c/5zW9+g2EY7N7tZOM4dWgBzgnbCA+kgLker5G9cfUWzxYFj5dJYCbZNbR4tXOPxcvMcZOo1Wj9JIWYAOZlomTU1h6zbAGcfvrpLFmyhBUrVrBy5UoWLVrEaaedFoRtgbIBsZGIipskn4CYxyCz8FMRWWEwUNcHTpDhr02I9bSS4C8ZFYwOorXyrmV59/DDD/PTn/6UoUOHMnToUKZOncojjzwShG2B0kLnMC/VkNE0BfULPxk12m3AXqLTRPcTGQWaOXpM1TTjBBnpC6I12MJSAHr16sWbb7555O+33nqLXr3isIHi0UQtNucEWQKgsg/6I6cVBOoPCLCDuSyxDH+p3n9mFxktJoiWvywF4NNPP+XOO++ksrKSyspK7rjjDj799NMgbAsUlcMfsgTgC8R6JUn2Aag/GsoOAxEdgNpf9jBnTcsSgKj4y1IApkyZwoABA5gzZw5z5sxhwIABoS3a5icqhz9SiGUMNku4lqqZWaYARCmD+oVsf6VQd/SYHWTMmjbZAPQG+km4llcsRwFt376dW265JQhbQmU7ooc/Kk0zJ6ToXMjMK1FqnjpBdoF2MiLDy/BpFJHtL3OvXBVHj9lBtr9A5LPtEq7nhbwCMHfuXAwj/7YacVsPCNSt+cmKTYLwwQRJ1woSma2gFkThfzJyOv2iiJetILuSHT7VAmBNtr/C3lorrwDcd999QdoRCVQOf8jawCSKG1fbQWYrKDscGGcB2Iuc1W+z/bVIwvWiiOw+JohGWZNXAN5+++0jv5eUlDBkyBA++uijQIwKixbga2Eb4YIKYL6ka2VvXL3B4rtRQsaQRhOVBwTYRfvLGTIFM0prj1l2Al900UUsXbqU+fNFETNmzBhefPFF3w0LgxZE7fe4sA1xQCmiQ0l2ZlatH0DWGG1Q1wdOkBk2/Jz4z52Q2Ro0iM7Ku5YCMGPGDGpqati+fTsAzc3NDBs2zG+7QsF8wYNDtcIZMpumoG5tTmaNth3ROaeaD5wgUwBA3f4zu8TVX5YC0NHRcdR+AEDBzmGViVJszi5aAKAvcltBEJ0M6gdFiEqOTH+p2n9mF9kCEBV/WQrAypUr+d73vkf37t055ZRT+MMf/sC7774bhG2Bo2LTX7YA7CZ6G1dbIdsHoO5wWDsMQIQ5ZXZwx9lfMmdNm0Rl7kReARg4UKyK85Of/ITTTjuN/fv388wzz7Bjxw5uvfXWoOwLFBVrvynEeiybJF5TtdqvXwKgkg+c4Je/zNFjceMkxDphsv11HOGvPZb3fS1dupQVK1bwzDPPcO+993LnnXcGaVco7EUsBqZSxk8hRhV0SLxmVJqndvGjQNuAqCmXAPskXjcKyNgKsisbUHP0mB38Sl8g3oWMuStuydsCGDx4MPfeey/nnHMOq1ev5oUXXuDKK6+kpKQkSPsCpwX4Z8Q2dyogOzYJwgdDEZlZBfxqBZnXjht+tQAAviXxmlHBT399k3DDQHkF4PDhwyxYsIApU6YwZMgQHn30USZNmsS6det48skng7QxUD5AbAzTBjwPfA/RwRhV/BCARsTqmq3A28BNiOZ9VPGjFaRiONAuKWA/orUri5WIhQSfAT4BfgtUSbx+mPghAJ8g+tr+B9EaeAD4BsGLga39Tzo6Ovjwww9ZtWoVO3fuZNSoUVJuPmHCBFavXs3HH3/MtGnTpFzTKz9GqPJDwJnA08BWYDZwJRC1hbD9mK36ODASuBMxz+BBROJ/E/g/hB+37IrMIaAmrZmfKg0JtksK8Xwyx/K1Zq7778AaYCqwBPgI+DVqTrA0qUC+YO4GKoHvI2ZP/xh4D/gMuA+okXgvK4x8RyqVMn72s58ZixcvNlavXm1Mnz7dGDlyZN7vOzm6detmrF271hg2bJjRo0cPY+nSpcaoUaMKntPY2Cjl3naPIjC+Bcb/gNEKhgHGbjBmgTEZjJ4B2pLr6JOx6T99vs9XwfhvMFZk7ncQjL+B8SMwBoTsA8BYDsZsydfsmXnWaRF4PtnHG2C86fM9TgBjChivgtGR8eVqMH4JxukR8IGT4ykw1vp8jz5g/ACMF8HYl/HXOjB+B8aZEq6fr+zM2wn8zjvvMHjwYGbNmkVdXR1LlizJ91VX1NTUsHbtWtatWwfAs88+y6RJk1i1apXU+3jBAN7NHP8BnA18F5gMXIFQ8Z8CYeyPVgSMz/wuu/bbldXArzLHaIQPrgT+H/AnoB5RgwmDf0IMP3xd8nX3ICaDhdUHUApMRPi7GLE4nXkU5/nd7namVcDLku3tyhfAo5mjDLgUkW5uB/4bWIfw70HE+k2HCvy+DpH/wmAQcDr+57F24KnMYb777wK3AP+J8MG/A29Jvm9eAbjttttYuHCh5Nt1MnjwYFpaOoMX6XSas84665jv1dXVcf311wNQVlbmmz1WHAYWZo5bgHOBx4DLCFYAahCF7xWIpukeYGmA9/8QmJE5TkfELr9PsAJwCuL5vwuMzXz2ng/3SRNsCKgvnRl/AmKY4AFE30Z2gdi1gMw+7NACBLmYyzZEJaEeMbLqMkTl5XiOFbMeiJFX5udlwCREWKS164V9YiBwOeI9nIsQ1v8b0L1BbDr/l8zRD/H838W/0VWhNKsuv/xyo76+/sjfV199tfHggw+6asaEdfwVERbx+z5nZpqCnyGahvsQTcUfIJqOYfpgasYmv+0YjgjHLM7czwDj72DcDMbJPt1zPhjv+/xcfcD4Phgv0Nn0Xw/GvWBUh/xuo3DUZnxyls/3GQDGDWC8DsahzD1XIEKfX42AH7wejkNAftPa2kpFRecYi1QqRWtrUBovhzTwrz5d+wyE6n8XGIaoCS5ANJ/nImoJUcBsGqcA2cG7oXTW9M/MfPYeIhzwV/xvlrciWjmy6Q1chHiuWkSNtwURTpuFGIlm+HBfFclOX+9LvnZ2aOo8RIvDDHfOQrR2k0Be1SgqKjKuuOIKXxSpe/fuxieffGIMHTr0SCfw6NGjXalYWMfPkF/7LQFjWea6B8B4BYxrwegXgefNdZydsfV8ydd9ks6a/j/A+CkYQwJ+tl8iOry7S7zmZDD2ZJ4rDcYDYHwTMeAg7HcZxaN/xle3SL7ubXR2Tq9Bzc5pJ0eBstP1iZ6P2tpaY82aNcbatWuN22+/3ctDhHJchUhAMpuI/5y55j2IxB/2M1odlRl7/13ydXeB8RIYQ0N8th9lnk1miKkejM8RwqkLfXvHbjDuk3zNdxGjx74WgecL4nAdAnrttdeYOnUqzz33HLt37z7y+Zdffml1qiXz5s1j3rx5nq8TFtnN09WSrmkuqDUH8O5h/9mY+SlztMwJiPkWryHGRYeFGZBM0fmcXqkA1gLvSLpeEkgjfzTWEERINewtGcPGUgCuvPJKAG688cYjnxmGwYgRI/yzShGyBUAWZq+IKlsRdiDWMomjD/yYDFZBcmLLspAtAMWI4Z1hp68oYCkAw4cPD8IOJTFrhTKXC6igs1BVhTTyfQDhLypmCrxMARgCvCrxekmgBfi2xOudjBjaGXb6igK2RgGddtppjB49+qiF4P7yl7/4ZpQqHEB+7XcIouZ5WOI1/aYFMTZfFmYYLOwa2jbEO5YlAP0QI4DCfi7VSNNZaMvIF1FJX1HAUgDuuusuvv3tbzN69Gj+93//l9raWv7+979rAcggu3nqx9o+fpNGbg2tAlHwtkm8phsMRCtPlgBEpWWjGmnEBLGTkNMyjkqIMQpYzh6fPHky48ePZ/PmzUyZMoUxY8ZQWloahG1K4IcAqFZApBGrh8paKM9c3M2QdD0vtCJPAHTN0x2y+9q0AHRiKQB79+7FMAwOHjxInz59aGtrO2oCV9KRKQBFmWupljBlx8qjJIIyBUAXPO4w05esUqcCMcJul6TrqYylACxatIjS0lLq6+tZvHgxS5Ys4b33/Fh5RU3SiGGLPSVcayDy92oNAtk1tCFExwfmMscyMENbKnXwR4E4p6+wsewDMId/Pvzww8yfP5++ffuyfPly3w1Theza78cer6VqDVFmBu2G8GVUfJBGhLZK8b78htnBH4XQlkpsQ2zLKVOIo5K+wiavAFRV5d/Pp6qqiqamJl8MUo3swk+WAEQl/GGX7AlTXhmI6PCLig+y5wJ4FQBd8LhHZqi1AviHpGupTl4BuP/++/OeZBgG48ePz/v/JCEzPqlqJ+F+xK5pcfRBtgB4ncBVgdhbQuMcWQLwFcQicFFJX2GTVwDGjRsXpB3KIrP2a67v/4WEawWNrAwatTCYrNnAqnbwR4U0cjacj1r6ChvLPoBrrrkm5+d6HoBgH6L2K6vwi0rowyktdNbevRC1DGrO9vYqAKp28EcFs4JRhLc+FFXDrH5hKQDV1dVHfi8pKWH8+PEsWbJEC0AWMmu/qhYQMmto7YjtAqOAuRm4VwHQBY830ggBHYC3CYJRq2CEjaUA3HzzzUf9XVpayrPPPuubQSoiSwCGAPMlXCcM0ojYagmiVeSWKA7RkzEUNGp9G6ph+i2FNwEw34NaW0/5h919pI+we/duhg0b5octyiJDAHoA5ahbQMiaDBbFVpCMvYF1zdMbsoYaVyDmYRzweJ24YNkCmDt3LoYhom7dunVj9OjRzJo1y3fDVCKNaJoejwgZuEH1FQqzM+gnHq5TATR7N0cqrXRuSemWCsTMUxX2eIgiMgVA1TzmB5YCcN999x35/eDBg6xfv165vXv9Jrv2+6nLa6geIpCRQY8jmuu0t9I5P6HD5TWiGNpSia2IWrsMAZC9d7XKWArA22+/HYQdSpNd+LkVANVDBDKGw5phlqj5wHy2QbivPUYxtKUSBuI9eJ1rYu4EphFY9gHs3LmTHTt2HHVs2LCBOXPm6L6ADDImg6kuAOb8hTj6QMZcAB168I7XvrZ+iP0Y9HvoxLIF8Pvf/550Os3TTz9NUVERV111FSNGjGDJkiU8+uijnHfeeUHYGWlkhD8qEAXobqsvRhivGTSqQyW9CoDqHfxRoQWo8XB+VCsYYWLZApg4cSKPPPIIu3btor29nfr6eiZMmMCsWbPo379/EDZGHrP266Xwi0OMuAXvPoBOQY0KXgV+MCKjqf5+w8ZrBUP1fjY/sBSAPXv2cMUVV1BUVERRURFXXHEF+/aJkd7m6CCNnNqv6glThg+2AXvlmCONLxE2uW0BRLVloxppxDyTE12er1sAx2IpAD/4wQ+45ppraGtrY8uWLVxzzTVcffXVlJSUcNNNNwVhoxLIKPxULyDSdC554IYoi6CXjWF0zVMOXltiFYhRXHo/hk4s+wDWrVvHxIkTc/7vnXfekW6QqqSBM1ye2xNRq1G9gDAz6MnAZy7Or3B5XhB4EQBd85RDtgC4mStSgXiPMjaWjwuWAlBWVkZdXR1Dhw6luLjz69ddd53rm06ePJkZM2YwatQoampqWLx4setrRYU0oqPPzVjxuBQQ2Rn0MxfnDwEWSrNGLq3AWS7PjWpoSzW8jraLQz+bbCwF4MUXX2ThwoW89tprHDp0SMpNV6xYwWWXXcbDDz8s5XpRILv2u97huXGJEXtpovdCbCwf1QzqNQQU1edSiS2IypWXEJDezPZoLAWgZ8+e3HbbbVJvunr1aqnXiwLZtRO3AqB6IeGlhhZ1EWylswPyc4fnukkTmmM5jFie240A6P0YcmPZCfzyyy9TW1sbhC05qauro7GxkcbGRsrKykKzwwovtd8hiMSt+gIbuxDbJrr1AUQ3g3pZ7C4OHfxRwe1gC70fQ24sWwC33HILt99+O/v376ejo4OioiIMw6C0tLTgeQ0NDZSXlx/z+R133MHcuXNtG1hfX099fT0AjY2Nts8LGi8CUEFn81Z13GbQqLeCsieDLXNwXi/gBKL7XKqRBsa6OC/q6SssLAWgb9++ri58/vnnuzpPVdpxX/uNUw3R7WSwCjqb+FHE7WxgXfDIJQ1c5OK8qIcYw8JSAAD69evHqaeeSklJyZHPFi6M6niN8PBS+10p2ZawSANfc3FeBaLwPyjXHGlsQgiUWwHQBY8c0nQOGHCytLYW4txY9gFcd911vP3227z66qv84he/4NVXX2XGjBmebnrJJZfQ0tLCN7/5TV555RXmz1d1H6yjcSsAcRolYg6HtVWzyCLqPjiI2InKqQBEvW9DNdyGWofQuWSLphNLAbjllluorq5m/fr1jBs3jqqqKrZv3+7ppi+88AIVFRWUlJRQXl7OBRdc4Ol6UcGNAPRH1GjiUkNMIxLVIIfnRXkWsImboaBRD22pRvbWkE5QIX2FgaUA7Nu3j/37xT5Xxx13HGvWrGHkyJG+G6YiaUTB56T2G7emqdsamgoZ1I3ARz20pRpe0ldcKlkysSyr0uk0paWlvPDCCzQ0NPDll1+yfr0e1ZwLs/Zbjv0VLeMWInCTQU9ELIcR9QzaCpzj8BwVhE0lNgOHcCcAr8o3R3ksBeCyyy4D4Be/+AVvvPEGpaWlsYnZyyZ7IpRdAYhrC8DJZDBVfNCKEKsSYJ/Nc4YQvT2OVeYQokPeiQD0IJpbjUYBR311envIwrip/VYg9jqNywqFOxATwpz6AKKfQc2hoCdjf+vPCuBlf8xJLE5DcScjWuZRb2GGgWUfgMY+bgWgFbHnaVxwmkFVGSrpdC7ACagR2lKNNPFsYYaBFgCJbMd57Tfqwx/d4HQy2BBgP7DVH3Ok4VQA4ta/ExVacCYA+j3kRwuAZNzUfuNWQ3TjgzTRbwU5FQBd8/SHNGJzd7trFOj3kB8tAJJxUvh1QxQmcUuY5nDY7ja/r8pImZ2IJT/svl9VQluq4TTUWoGYALbbH3OURguAZJwIQFxXKEwjRhcMtPn9IahTSDqZDKZKaEs13AhA3PKYLLQASCZN56gDK+LaNHWSQVVrBTkRAFVCW6rhVADi2M8mCy0AkjFrv8cuhH0scQ0ROJkLYK4bpEoGdSoAcXu3UWAjYnkNux3B+j3kRwuAZJzUTnQLQD0ftCJaeEU2vqtrnv5wEDFvxk766omYvKffQ260AEjGSeE3BNEx5WRZWxX4ArEBul0fgDo1tFbEzNIBFt9TLbSlGnb72lSrYASNFgDJOK39qlLwOSWuGdTu1pBmaCuu7zds4pq+gkYLgGQ+x37tN86jE+xOBqugczc1FTDnAlg9m5585C9OBUALcW60APiA3cQZ5xixEx+olDntTgbTNU9/SQP9EBPCCmHux9Bq8b2kogXAB+wUfj0Q4+TjWkCkEYWkVWepaq2gLYhOSLsCoJK4qYTdUOsQxDvr8NccZdEC4AN2BGAw8V6hMI0QuZMsvqeaABxGjECxEoAhiJnDO323KJnY3Rkszv1sMtAC4AN2ar9xDxHYqaEdh+gsVc0HduYCqCZsqmG3BaDfQ2G0APhAGlG4Far9xr2T0M5kMDPzqlZDsysAqj2XSph7LNsJAcU1j8lAC4AP2Kmd6BaAuj6wE+LTBY+/HEDE9gu9h/5AL/R7KIQWAB+wW/h9Duzx35xQ2IZYCC2OAtAKlCIKl1wcR7w7+KOClRDrjnhrtAD4gB0BiHsN0UAUlFY+APv7J0cFq6Ggqoa2VMOuAMQ5n3klFAH43e9+x6pVq2hubmbOnDmUlpaGYYZvbMVe7TfuCdNqMlgFwld7gzFHGlYCEPf+nahgtTOYfg/WhCIADQ0NnH766YwZM4aPPvqIn//852GY4Rt2ar9J6CS0U0NTMXNaCYCueQZDms59l3NRgegr2ByYReoRmgAcOnQIgH/84x+kUk42EFSDQoVfL0TCjXsBkXQBUC20pRpW6zJVIN6V3o8hP6H3AUyZMoV58+aFbYZ0ChV+SakhpoHjgbI8/1dtGQiTPYgVXAuFgNqAfYFZlEys+tpUrWAESbFfF25oaKC8/NhtUe644w7mzp0LwO23387Bgwd56qmn8l6nrq6O66+/HoCysnxFSfRIA5fl+V9SRidkzwXY1uV/vRFruaiaQQuF+HTBEwxWAjAEeDcgW1TFNwE4//zzC/7/2muv5aKLLmL8+PEFv1dfX099fT0AjY2N0uzzmzRQgqj9di38ktQCAJFBm7r8T3UfFJoMVgGsDdCWpFJoZdYixPuJeyXLK6GEgCZMmMB//dd/MXHiRPbuVW0MiD0K1U6SskKhlQ8gngIQ9yG+UWEfonKVayTQQMR8DP0eChOKAPzxj3+kT58+NDQ00NTUxEMPPRSGGb5SqPAbghiZcDA4c0KhDbEKYz4fgLo1tFbEOkbdu3zeBzFJTBc8wZBvqLEeAmoP30JAhTj11FPDuG2gWNV+VS34nHAYsWZLPh8conNNF9VoRRT+Azn6GZLSvxMV8g220O/BHqGPAoor5hrk+RJnUmom+WpoFcAmhAioSL6hoLrmGSxWAqDfQ2G0APhEodpvkmLE+TKo6j7INwZdFzzBkgYGIIYbZ1MB7EYM19XkRwuAj+Qq/MyZi0kpIArV0FRunucbgVKB6NvZFKw5iSWfEKtewQgKLQA+kqvwS1psMo0QvP5dPlc9DLYNscxAroJnI+qGtlQj374TqlcwgkILgI+kyZ0wQe3Czwm5MuiJwFdQ2wcGoqDPFQJS+blUI9/WkPo92EMLgI/kqv0mrZMw12go1YeAmuSaC6BrnsGSKxTXAzW3Gg0DLQA+kqvwM1co3BK8OaGQzwegfgbNJwCqP5dK7AG+4Oj0NRhRsGkhtkYLgI/kK/zSJGeFws2IeHgcBSDN0QIwALH8h+rPpRpd+9rikr6CQAuAj+QLfyQpYR5CjIjp6oP9iM1gVKYVsahd38zfSevgjwpaANyjBcBHzIlOXRNn0hJm18lgpg9UbwV1jT8nrX8nKnQVAP0e7KMFwEe61n67kcwVCnPV0OKQObvOBtY1z3BoQXT6Hpf5uwL4HNE/oCmMFgCfyS78BiJGKCStgOg6HDbOArCXY5f/1viLGWo9OfMzLukrCLQA+Ex24ZfUpmkaESsvJV6tIHMROFMAkta/ExW69rVpAbCPFgCfyRaApHYSZmfQQYglaOOQQfcjavvZLYA4PJdqdBUAVbcaDQMtAD5j1n77ktwYcXYGjZsPsoeC6klg4ZCdvnoi1tuKS/rym1D2A0gS2YlzCLAL2B6aNeGQ7YPSzO9xyaDm3sDdETHouDyXSuwCdhDPCobf6BaAz3St/SYxYW5CLI+dnUHjUlM2ZwOfjBCBJL7fKNCCSFtJ7Wdzi24B+ExXAYhLweeEDsTSFynEGu07M0ccaEWM7hqR+VsXPOFgjraLWwXDb3QLwGc2cnTtN6kFhDkZLG4+MIeC1mR+6oInHLIF4DCd70VTGN0C8Bmz9jsCMQImToWfE9LAPwH7iJcPzILmG5mfcXo2lUgjJoMNR6w/dTBcc5RBtwACIA2clfk9qTXE7BpanHxghvi+iejc3xWeKYkmjSjMziJe6ctvtAAEQBoYmfk9qTXENNAPES+Pkw/MFkA5uuAJE1OIRxKv9OU3WgACIJ31e1ITZ1x98CVi+QeI13OpRkue3zWF0QIQAHEt/JyQ7YO41ZTNVkBS320U0HnMHaEIwC9/+Uuam5tpamri1VdfZdCgQWGYERhm4txGZ20xacQ5g5oCEDdhU4mdQHvmd/0e7BOKANx7772MGTOGqqoqXn75Ze66664wzAgMs/CLW8HnhI1Zv6fzfktNdAsgGuh85pxQBKC9vf3I77169cIwVN8apDA6YYqF09oQu4DtC9kW2WgBiAY6nzkntHkAv/71r/nhD3/Ijh07OO+88/J+r66ujuuvvx6AsrKyoMyTii4gBC1AUdhG+ID5XteHaoUmDRxAzLvR2KMIn3bma2hooLy8/JjP77jjDubOnXvk79tuu42SkhJmzJhhec3Gxkaqq6tlmhkY/wG8DjSHbUiIXJL5+UKINvhBP+Bi4C8h25F0ajLHH8M2JIIUKjuNMI+Kigpj+fLltr7b2NgYqq360Ic+9KHika/sDKUP4JRTTjny+6RJk1i9enUYZmg0Gk2iCaUP4O6772bkyJEcPnyY9evXc8MNN4Rhhkaj0SSaUARg8uTJYdxWo9FoNFnomcAajUaTULQAaDQaTULRAqDRaDQJRQuARqPRJBQtABqNRpNQfJsJ7AdtbW2sX+9uwn1ZWRnbtm2TbFE0iOuz6edSj7g+m+rPVVlZyUknnZTzf6HPUgviiPMs4rg+m34u9Y64Pltcn0uHgDQajSahaAHQaDSahJIYAXjkkUfCNsE34vps+rnUI67PFtfnUqoTWKPRaDTySEwLQKPRaDRHowVAo9FoEkoiBGDChAmsXr2ajz/+mGnTpoVtjjTWrVvHsmXLaGpqorGxMWxzPDFz5ky2bNnC8uXLj3zWv39/FixYwEcffcSCBQvo169feAa6JNdzTZ8+nXQ6TVNTE01NTdTW1oZooTtSqRSvv/46K1euZMWKFdx8882A+u8s33PF4Z3lI/SxqH4e3bp1M9auXWsMGzbM6NGjh7F06VJj1KhRodsl41i3bp1x4oknhm6HjOPcc881qqqqjtod7p577jGmTZtmAMa0adOMu+++O3Q7ZTzX9OnTjalTp4Zum5ejvLzcqKqqMgCjd+/expo1a4xRo0Yp/87yPVcc3lmuI/YtgJqaGtauXcu6devo6Ojg2WefZdKkSWGbpenCwoUL+eKLL476bNKkSTzxxBMAPPHEE1xyySUhWOaNXM8VBzZv3kxTUxMAu3btYtWqVQwePFj5d5bvueJK7AVg8ODBtLS0HPk7nU7H5oUahsGCBQtYtGgRdXV1YZsjnYEDB7J582ZAZMyBAweGbJE8brrpJpqbm5k5c6ZyYZKuVFZWUlVVxfvvvx+rd5b9XBCvd2YSewGIM+eccw5f//rXqa2t5cYbb+Tcc88N2yRfMQwjbBOk8NBDDzFixAjGjh3Lpk2buP/++8M2yTW9evVi9uzZ3HrrrbS3tx/zf1XfWdfnitM7yyb2AtDa2kpFRcWRv1OpFK2trSFaJI+NGzcCsHXrVp5//nlqampCtkguW7Zsoby8HIDy8nLa2tpCtkgObW1tHD58GMMwqK+vV/a9FRcXM3v2bJ566imef/55IB7vLNdzxeWddSX2AtDY2Mipp57K0KFD6dGjB1dddRVz584N2yzP9OzZk969ex/5/d/+7d9YsWJFyFbJZe7cuVx77bUAXHvttbz44oshWyQHs4AEuPTSS5V9bzNnzmTVqlU88MADRz6LwzvL9VxxeWe5CL0n2u+jtrbWWLNmjbF27Vrj9ttvD90eGcewYcOMpUuXGkuXLjVWrFih/HM9/fTTxsaNG40DBw4YLS0txpQpU4wTTjjBeO2114yPPvrIaGhoMPr37x+6nTKe689//rOxbNkyo7m52XjxxReN8vLy0O10epx99tmGYRhGc3Oz0dTUZDQ1NRm1tbXKv7N8zxWHd5br0EtBaDQaTUKJfQhIo9FoNLnRAqDRaDQJRQuARqPRJBQtABqNRpNQtABoNBpNQtECoNFoNAlFC4AmkZxwwglHlvbdtGnTkaV+29vb+dOf/iT9fo899hiffvopP/rRj/J+55xzzmHlypVHLR2t0fhN6JMR9KGPMI8glvp97LHHjMsvv9zye5WVlUctHa0Pffh56BaARpPFv/zLv/DSSy8BYhOQxx9/nLfffpvPPvuMSy+9lHvuuYdly5Yxb948iouLATjjjDN48803WbRoEfPnzz9q2YB8TJ48meXLl7N06VLeeustX59Jo8mHFgCNpgAjRoxg3LhxTJw4kSeffJI33niDr33ta+zdu5cLL7yQ4uJiHnzwQSZPnsyZZ57Jo48+ym9+8xvL6951111MmDCBsWPHMnHixACeRKM5luKwDdBoosy8efM4ePAgy5cvp3v37syfPx+A5cuXM3ToUEaOHMnpp59OQ0MDAN27d2fTpk2W133nnXd4/PHHmTVrFnPmzPH1GTSafGgB0GgKsH//fgAMw6Cjo+PI54cPH6a4uJiioiJWrlzJt771LUfX/fGPf0xNTQ0XXnghixcv5utf/3osdw7TRBsdAtJoPLBmzRoGDBjAN77xDUCsJT969GjL84YPH84HH3zA9OnT2bp161F7Vmg0QaFbABqNBzo6Opg8eTJ/+MMfKC0tpbi4mN///vd8+OGHBc+79957OfXUUykqKuJvf/sbzc3NAVms0RxN6EOR9KGPuB96GKg+onjoEJBGEwA7duzgV7/6leVEsJdeeolt27YFaJkmyegNYTQajSah6BaARqPRJBQtABqNRpNQtABoNBpNQtECoNFoNAnl/wNOF+UC/J186wAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "waypoints = [   \n",
    "        [3,3,np.pi/2],\n",
    "        [6,6,0],\n",
    "        [3,10,np.pi/2],\n",
    "        [10,20,0],\n",
    "        [20,20,np.pi/2],\n",
    "        [40,40,0],\n",
    "        [20,40,0],\n",
    "        [80,80,np.pi/2],\n",
    "        [90,90,0],\n",
    "        [100,100,np.pi/2]\n",
    "        ]\n",
    "R = np.array([[0.01,   0],[  0, 0.01]])\n",
    "trajectory,controls,waypoints_reached,error = get_control_waypoints(waypoints,R, dt = 0.5,error_th = 1, verbose=False)\n",
    "get_animation(waypoints,trajectory)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "MovieWriter imagemagick unavailable; using Pillow instead.\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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TJjBz5sxIyiEIgkuIJnwE0oHNTQSdoWfEiBFq9+7d6o033lBvvvmm2rVrlxo+fHjYM/xkZWWp4uJi//+lpaUqPT1dASo9PV2VlpYqQL366qtq3LhxjW4XyGTmNTEx99k7oDZHsd8SUOtd4H9TsGDPzpBjH3300Uf07t2b/v37A/Dwww/z5ZdfhtotIGlpaVRX67RSdXU1aWl6GKyMjAwqKir821VWVpKRkeHf1kdubi4TJkwAICUlJWo/BEGwhmjCR6BrCpeb7IsQOSFFAWDAgAEMHjzY///f//530xwINxTlIy8vj7y8PAA8Ho9pfgiCYA4tiC58tBdIRce060z1SIiEkDmFZ555hkmTJrF582Y2b97MpEmTePrpp6M+YU1NDenpOnKYnp5ObW0tAFVVVaflLjIzM6mqqor6PIIgOEMsNYVmgNT/nSWkKIwePZprrrmGWbNmMWvWLEaOHMl1110X9QkXL17M+PHjARg/fjzvv/++f/2dd94JQL9+/Th06NAZoSNBENxPLKIAkmx2mrDCR8nJyXz11VcAp/VZCMXcuXMZMmQIKSkpVFRUMG3aNJ599lnmz5/PPffcw+7du7nlllsA+PDDDxk9ejTl5eUcOXKEu+66K4riCILgNC2AQyG3OpP6Q11sNM8dIUJCisIzzzyD1+tl1apVJCQkMHjwYH8z0lDcfvvtja4fNmxYo+snTpwY1nEFQXAv0dYUZKgLdxBSFObNm8cnn3xCnz59AJg8eTI1NTWWOyYIQnwSrSj4nioiCs4SUBQa9iiurKwE4IILLuCCCy7A6/Va65kgCHFJtK2PjgBfI6LgNAFF4YUXXgi4k1KKq6++2hKHBEGIb6KtKYDMwOYGAorC0KFD7fRDEISzhFhEQYa6cJ6QTVLPOeccfvWrX/HnP/8ZgO985ztce+21ljsmCEJ8Em34CEQU3EBIUZg1axbHjh1jwIABgO5k9tRTT1numCAI8UmsNQUJHzlLSFHo1q0b06dP5/jx4wAcPXqUhIQEyx0TBCH+SCC6+RR87AXOA1qb5pEQKSFF4dixY7Rq1co/RlHXrl3573+j/coFQTibaW4sYwkfAaSZ4IsQHQFF4ZVXXmHgwIE8+eSTLFu2jM6dO/PWW2+xYsUKHnvsMTt9FAQhTmhpLGMJH4HkFZwkYOujsrIypk+fTqdOnVi+fDkff/wxhYWFTJo0KaahswVBOHsxSxQkr+AcAWsKL7/8MgMGDODKK6+kvLycG2+8kRdeeIEHHniA7t272+mjIAhxQgtjGW34SIa6cAdhz9bTq1cvVVhYqE6cOOH4zEGEmD1ITEzMfssGpUDdGeX+iaBOgPqtC8pyNluwZ2fIRHOzZs247rrreOutt1i6dClbt27lxhtvDLWbIAhNkFjDR3VALVJTcJKAOYVhw4Zx2223MXr0aNauXcu8efOYMGECR44csdM/QRDiiFjDRyBDXThNQFF4/PHHmTt3Lo8++igHDx600SVBEOKVWGsKIL2anSagKFg14F2PHj145513/P937dqVJ554guTkZHJzc9m3bx8AU6dOZenSpZb4IAiCNZglCt83wRchOsKaec1MysrK/MNyJyYmUlVVxaJFi7jrrruYMWNG0NFZBUFwN2aEj6rRndcS0JlPwV5CJpqt5Oqrr2b79u188cUXTrohCIJJmFFT2IvuGd0xdneEKHBUFMaNG8fbb7/t/3/ixIkUFRWRn59PcnJyo/vk5ubi8XjweDykpKTY5KkgCOFgVvgIJK/gJI60k23evLnat2+fSk1NVYBKTU1ViYmJKiEhQT311FMqPz8/pra2YmJi9tst6H4KPWM4xiDjGMNcUJ6z1WLqp2AVo0aNorCwkNraWgBqa2upq6tDKUVeXh59+/Z1yjVBEKLEzJqCNEt1BsdE4bbbbjstdJSefqqyOGbMGEpKSpxwSxDimi7AMAfPb1ZOASR85BS2tz4CaN26Nddccw333nuvf93zzz9Pr169UEqxa9eu0z4TBCE8JgMTgOHACgfOb0bro2+BbxBRcApHROHIkSNnJInvvPNOJ1wRhLOKNHT1fw6Qw6m3brswo6YA0oHNSRxtfSQIgrl0BLYDbYC3gWY2n98sUZChLpxDREEQziI6Al7gPuBK4H9sPr8Z4SOQmoKTiCgIwllECvAlOnyUB/wKGGnj+VsCx9FtG2NBRME5RBQE4SyiA1oUAB4CioA3gUybzt+S2ENHoEWhPdDKhGMJkSGiIAhnCeehh4fwicJ/gJvRD+o5NvnQgthDR3AqQZ5mwrGEyBBREMImCbgUuBOYAXwI9HPUI6E+vrGC6s+gvg34X2AwcL4NPphZUwAJITmBI01ShfiiJVoABnCqOn8E/VZYDqxxyC/hdHyisL/B+rXG8lJgpcU+iCjEP1JTEELSDRgKLAFuB3oC5wL/Ai530C/hdHw9f75ssH6jsbRjjgKzwkcy1IVzSE1BCIkvrvtH4NN669cD96Lbwp+02ynhDBoLH4GuOewFLrPBB7NqCrXo+ZqlpmA/UlMQQpJqLGsbrF8PtAa+a687QgACiQLo2oIdNQWzROEksA+pKTiBiIIQkmCiABJCcgsd0W/XBxv5bCNwMdb3cDYrfASwA+hu0rGE8BFREEKSCpwADjRYX4YeuExEwR10RH9HdY18thH9Ft/DYh/MqimAfbUb4XREFISQpKKr8g17qdahh1QQUXAHvt7MjWFXstlsUegIXGDS8YTwEFEQQpLGmaEjH+uBXsiN5AY6ElgUStHDT1gtCmaGj4qNpdQW7EV+y0JIUgkuCm2QZLMbCCYKx4AtxFdNQUTBGRwThZ07d7Jx40a8Xi8ejweA9u3bU1BQQFlZGQUFBSQnJzvlnlCPUKIAEkJyA8FEAeyJ0ZspCgeBL9Cd7uKF9sAHxLeQOVpTuOqqq8jJyaFPnz4ATJkyhRUrVtCjRw9WrFjBlClTnHRPMEgFagJ8thVJNruFjpzZm7k+G4ELgWQLfTAzfATxl2y+HLgWWIQWiHjEVeGjG264gddffx2A119/nR//+MfOOiRwDrr3cqCaQh2wAREFp2mFDuOFqimAtW/eZtYUQPvcEz3QXzzg61fRFT0IoasesGHimM9KKQoKCli3bh25ubkApKWlUV2tO7hXV1eTliZjJDpNoD4K9VmPnvoxHn8AZwvBOq75sKMFktmiUIwWhHjJWflE4RfAKGCag75Ei2PDXAwaNIg9e/Zw/vnns3z5ckpLS8/YRqkzp+rIzc1lwoQJAGfM8yyYT7iiMAm4CJ3MbGr0A9bh7FAf4YjCXnR4yUpRsCJ8BNrn4mAbuoROwGH0KMKXAE8AHnSeIV5w7OVuz549AOzbt49FixbRt29fampqSE/Xo52kp6dTW3vmoygvL48+ffrQp08f9u8PFkEVzCBcUYCmGUKaDKxGi6KThCMKYH2M3uyaQplxvHhJNnfi1FwQD6J/G2+iB5WMFxwRhdatW9O2bVv/38OHD6ekpITFixczfvx4AMaPH8/777/vhHtCPXyiECjRDLoN/Lc0PVH4OfCs8fdoJx0h8LDZDdmIfsAmWOBDEvqBYmZN4QSwmfhJNtcXhf8AN6FrkIvQ44TFA46Ej9LS0li0aJF2ICmJuXPn8tFHH+HxeJg/fz733HMPu3fv5pZbbnHCPaEePlHYF2SbpphsHgO8ip5nogx4AJ3o/dYhfwINm92QjWg/u6HnwjCTFsbSzJoCaJ+HmXxMq+jEqZozwG70cPMfAeOBmU44FSGOiMLOnTvp1avXGesPHDjAsGHx8vU3DdLQMdKjIbZbD9yNflNsbOyds4mrgLfRkwvdDPQHHgaGAH93yKdIwkeg37zNFoWWxtJsUShGP1BD9cNwA/VrCj4K0OIwlPgQBWkwEkfcgb7B7FTyYB3X6rMeaIv1A645zeXA++hpLq9Dz0D3T3QNYaSDfnVEi/fxENttRoczrAjH+ETBzPAR2NOU1gzaGtZQFEDPeDcEa8J2ZiOiEEeMBq5Bx7LtIhJRgLM7hNQOWIqO248AvjLWHwNWGeucIty36KNoQbNCFKwMH4H7RcHXHLUxUViFDvG5vQwgohBXdDWW09BxYTsI1pu5PqXot+azWRR6A+cD9wN7Gny2DD32f9eGO9lEqN7M9SnC2pqC2aJQg34xcXuy2ScK1Y18tspYXmWTL7EgohBHdEW/kaejY9h2EG5N4SRnf7I521hubeSzj4ylU7WFYMNmN2QjOtHc1mQfrAofQXwMdxGsplCJrqENtc+dqBFRiBPORb+lvoNu3vYYp1qcWEWCcc5wRAFO9WyOh7hpNHRFN5GsaOSzcmA7zuUVIknC+sIxl5jsg1XhI9A+X4K7H1jBRAF0XuFKrJ/9LlbcfI2FevjCEjuAqejw0VSLz9kBndQOVxQK0eJ1tiabs9GjdgbqufwR+k3QiXF6ohEFs9+8rQofgW6B1Bp3dwLrhC57wxkKfaxC56VybPMoOkQU4oT6olAKvIbuMdnFwnOG03GtPmd7srkr+voHYhk6JDPQHnf8NEOPyBluTuEL4BDWiYJV4SNwd6K2E43nE3zES15BRCFO8InCdmP5JPqN9bcWnjOcIS7qsxndNHOANe44TjawM8jnq9BNQu0OIfmGaI6kDb8VMXorw0dWNqU1i8b6KNSnFtiE+/MKIgpxQlf0j/5r4/89wEvAT7DuhxKpKJwElqPb759ttEF35AtWU/gG3WfB7mRzuL2Z62OFKFgZPvoPuud4PIsC6LzCINw9FLiIQpzQWOjiOfTsVM9YdE7fwOXhigLo0SCzcHc1Pxq6GMtgNQXQIaRe6BZidhFub+b6rEfHt838nqwMH4H7WyCFIwqr0CHGPta7EzUiCnFCN84UhYPA79Gd2qxoH5+KfvsPlDhrDN8wD2dbbaF+TicYvqapwy30pSHRiMIyY3mtiX5YGT4CnWzuhn19dCKhJbphRihR+BQ9DIyb8woiCnFAIvpNtbEH0lxjOcaC86aiB8KLZCyjamAt8CML/HESXx+FUKJQhH4w2JlXCHeE1PrsRc8BYaZ4Wxk+Auua0pqBr2YYShQOoO8RN+cVRBTigEx0DLKxB9JudCjgRgvOG27HtYYsQU88c7657jhKV/TYQuG8jReghyOx68cVTU0BdK3uh/X2jxVfTcHK8BG4M4QUriiADiEN4JSIug0RhTigYcujhixE32SdAnweLWlEJwofoG8sM0MTTpNN6FqCj2Xo5K9dTXNT0G/nkQ7b7fueRpnkh9U1hd3ohhZuFIVQHdfqsxI9p/YPrXMnJkQU4oBQ8eyFxvLHJp832prCBnSvX7tCSBeipz+cjXW9qbsSOsnsYzk6F3O9Rb40JNohpdejw31mibfVogDa5yEWHj9aIhGFz9D3h1tDSCIKcUA3dPv3ygCfl6LnRjY7hBStKIB+Cx3OqZCCFXwfPdXhdvRYUOOxLpYfSU3hS3TC+WfY8wOLVhQUOoQ0EnOGY7c6fATwN3ROwW2t2zqhH/Th/F6+Rudz3Jpstl0UMjMzWblyJZs2baKkpISHHnoIgGnTplFZWYnX68Xr9TJqlFmV2vinK7rqHGxi+IXoN6gOJp2zFXAe4fdmbsgSdNO7ISb5U5/u6BBNEXAD8CL6GlUCj1pwvlR0i5dwawoAf0XnguzosxDJCKkN+QBIxpxe2C3RjRJOmHCsQMxHvyDdbuE5oqETWhDCbZSxCp13c2NLKtAvDLZZenq6ysnJUYBq27at2rp1q+rZs6eaNm2aevTRRyM6lsfjsdV3p2wNqI9CbHM5KAVqvEnn7Gwc7+4o928F6ltQf7DgevwN1CFQU0C1q7f+l4bPl5l8vn7GcUdHsE9zUNWgFlpQ/oZWYlyTaPZtC+o/oKab4MdzoI7YUN4PQO0ClWDDuSLxaX0E21+DvqdGOORvsGen7TWF6upqvF4vAN988w1btmwhIyPDbjfiiq4ETjL7WI8e08asEFI0Hdfq8x90bN2KvMIP0TWRZ9Fj+Pj4C7qFkNm1BV9OZ2cE+xwHXkeXPy3EtrESybDZDfkG3XbejKapLbA2dORjLrqDpN1jTAUjnI5r9fkcfe1vtsadmHA0p5CVlUVOTg5r1qwBYOLEiRQVFZGfn09ycnKj++Tm5uLxePB4PKSkWD14tPOch/7RhxPPXoiO45sxTn6kQ1w0xhL0j9fMduUZhq1u5LNDQD4wztjGLHx9FHZFuF8+OlY/3kRfGqMDsc1d/AHwXWIfgbQl1iaZfbyPbmnlphBSpKJwBHgLXYb2IbZ1AkeqL23atFHr1q1TY8aMUYBKTU1ViYmJKiEhQT311FMqPz8/pirQ2WKXoauZN4ax7RXGtjebcN6fGcfqEsMx0o1jPG7i9bjJOOYPAnzeBdQJUM+aeM6/gtoT5b6fgioz0ZeGdp5xPX4RwzG6Gsd4KEZf8kF9YWFZ69scUPvRYTo7zhfMEtH33G8j3O/7xnV/xAGfXRU+AkhKSmLBggXMmTOHRYsWAVBbW0tdXR1KKfLy8ujbt68TrrkO39tbODWFz9Fv9maEkMyoKVQDHswNIfVHh6aKAny+C1gA3It5M4tF0vKoIX9FJ8YHm+RLQ6LpzdyQHehRSGMNIdkVPgIdQuqIvcOJBCIVPXx5JDUF0J3x/ome3tVNE1M5Igr5+fls2bKFGTNm+Nelp58aQmzMmDGUlJQ44ZrrCHfMHdAtH95DtzuPtbdkKjrmeSTG45jdu7kfejKf40G2eQHdouZuk84ZSR+FhryLDmv93CRfGhJtb+aGfICeFezcGI5hV/gIdJPf/bgjhBRJH4WG/BH90nCNee7EjO2iMHDgQO68806GDh16WvPT559/no0bN1JUVMRVV13FI488YrdrrqThkNmhWIj+YQ+L8bzR9mZuyBL0TTbahGMlAT8A1oTYbi36DexhYp/6MAnoTPQ1haPAHGAsWqjMJpphsxvjA/SbfiwPJztF4QS6z8INON+sMxZRWIhu9v2Aee6YguMxuWitKeQUlqGbpIa7fXNQB9Hx3VjO+xGof5tUhp2gVptwnBx0DPaWMLb9sbHt2BjP6Yu3/8wEvx8w6XrWt58Yx+4e43GagToA6rUYjrHUpO85XBtolP12G8/ZmN1j+HFhlPs/hc5JRLt/NOa6nEJToRWxh3FCTQHZkOPot/MbiG0ij1h6MzfkSXTY55YYj9PfWDbW8qghi4FyYm+eGu7oqMHwokNeuTH60hhmhY9OojsEjib6+LadNQWAf6E7dTodQvLVFIJNxRmMPxvLe03wxQxEFOphdrLn38BXwFJ0KON7Ee4fbMjsYLyJfljcF+F+9Ukl+t7MDXkTPR7Ss8Q27EV/9A/vizC2rQOmG/vcFsM5o+mj0Bh/RU++0zvG4zSkI/qBftCEYy1Chw1vjXJ/u0VBAW+je4072Ti9E1qUo02yV6Bf5H6OtcPChEuTFIUk4GJ0e/an0MnZ7ejEqllvc33QD4FP0W31Z6DnZ/0CmBjmMToTeMjsYBSgO449SXRtoBPQiWGzagp1wP9Fv3X/nxiO04/wagk+/mps/zLRPzSy0T/2qij39zEXnbSfFuNxGtIR/eIRyZwXgViA7gQ5HWgdxf52tj7yMQf9e3ayE1ikfRQa40/oF7GbYncnZpqkKPQDStBvGZOB76CbTnrRrQEGmXCOn6KTjLeiawgXogVnB/AHwku8RtLyqCG/QE+3GM1DqD1ajMwSBYAVwIfAr4lufKb2wEWETjLXpw64B90B8KUozgmnxp2K9aF7CF3264G7YjxWfWLpzdyQOuAh9JhNj0exv901BdC/42J0s06n5j02QxQ+Rs9B7ZaEs6NJmlgs2kRzW3Ry6lJQLeqtbwdqK3rMmowY/EoCVQtqXiOftQJVCOpLUFkhjhNrAmsmqGOgLopwv+8a5x1n8vd1MTqhNiOKfUcYPg2JYt/fGPteF8W+a9DJfjPKnwBqBaivQWWbdMzloD43+Xt6E9TRKHzcCmquyb6EYz8yvt//deDcoMdhet2E4zxslOP7Nvgc4tnpzIW0oWBRWU/0j3YNqJZRHuNagj+EuqJbCK3hdFFqaE+jH+qJUfpxvnGeJRHuN9jw/yoLvrM/G2X6ToT7TUMLStsoztkc1EZQFegewJHsuw8trmaVv7Pxnfwjhu+1vhWCWmzyd3QBqMNEPpjfTlCzTfYlXPszqJPoXv2R7hvt79xn/8GcHvTJxnX/BP1iaeX1ktZHEbAFHfrpi47zRcMd6I41ywJ8vgM91n5f4PdBjtMV3UM32tDFPuBpdE/VSPotmNGbORBPoEMMz0S4X390TuabKM55HB1G6gQ8F8F+5xL+uFPhUoHOq1yBOQP3xTJsdiD2oO+bMUR23zgRPvLxC3Re8E10uDBcnkPni7KiPG8HdLljDR+BbiwwAd2JcLoJx4sFR5TdDLOyn8L/EF3b8vPQwweHM2T07wne7n4tsYcuWoDajn5TbhbmPg8Yfp1v0bX9tXH8AWFun4AOt/05xvNON847OMztfWPTxNrXoTH7G6j/Enuo4BvMGfa6obUEtQ3UJsJ/a/0S1MsW+BKu9QV1HNQbYW7fD127UKA+JrqhuC8m/L4z4doLxjHvsPBaSfgoCktAV8uPgRoVwX53GV9o3zC2TQL1T3S4qkcjn+8H9ScTynKj4dO9YW7/P+gfixnhjcasNahKULsJr9NVD2Kb28Fn54AqRw9QF47g3WCct7cF16AjqL2giggeQgxmrQz/plj0Pfli9ZPC3P4w+kXHCl/CNV/+6NYQ2zUHVYwewO8RY5/7ozjfMGPfaMJWgawZqJXol0sr7j0QUYjazkPHbE8Qfo1hBTrhFu45MtBJ6e2gvldvfTv0zfZ/TSrLJ8Z5wklazwRVY/F3d5lxjhp0j99g2/7UuBbfM+G8g9CT/2xH54+Cbet7WLS36BqMNo7/FvoBH+n+Gcb+uRZ+T0tBfUV4jRWOofNgVt43oawZqH+he2dnBtnuCU6fOGkZutYVaXLdd29GmiMLZSnol6Zdxt9mXycRhRisDaj3jS/+ZYKHYDLRb9i/ifAcP0APzfw1+u0MUL2Mc44xqRyXon/cewk87LTPFqDDTVZf2+7om/4gwd+0/oieac2smovven8F6uog271sbGPlNZhqfM+FRP5A8oW3whlWPVr7Dro13lfo2cICbZdg+PKExdcrHOuGrrWspvFWhD3Robs59dZlou/DT4gsjPSYUe42FpSjN7oV2ArCD/2GayIKMVoip+LRSwncgsV3g0TT3PACdA7hJPpB4Zs34DITy9ET1A70m/KPg2z3GTrGase1zQS1GV1VDjTd5Xp000szz9sZLXzHQf08wDYfoB/WVl+D0eg32wNE1mz2KiLLkURrF4LaYFyriQG2aYm1oaxI7cdoYfiS00UzEd2Edx9nvoH/zChDoDI2ZjPQL3NWlcNXE1mEnp/ErOOKKJhkP0dXkUtoPEFYjM4RRHv8Vug24gpUlbGMtAllKEtFD3R3EtSjAbaxu715CiiPcW0f4PSJU85BP4x+Z8F5zwX1oXGdpxvnqv/5JlDv2nQNuqDFT6EHSAunVjTW2P5iG/xrg34wKXR4sWHy2TfZjxMTxgSy76CbfStQeUYZJhI8ifsB+qWpW5jnmEdk4eJo7GF0jeEgqPswZ25qEQUT7Sr024dCP1CGGOt7EVkyN5j9Ev3Q3mdRGVqBesfw91V0/qL+5wdBvWjzdT0XXRtQ6FjqRPRDehDRdzwLx5qBesU4xz50kj3V+OwI1rTsCWQtQf3F8KUI1ASC98u4z9jWzDfIYJaA7iCm0CGN+i9G52PdSLCxWBJaZE+iH96H0bX9QNtfgA6V/ZPwQkKfokNOVpejG6d+H58T+4uAiILJ1h4d4qk2vqS1aIH4L6gOJp3jSnQnOKvKkIBOCir0m9Fr6CZ6vjDAVIe+05Hojl0KnYReibXNY312Baj30A+Po+h4syK6Fimx2q2gvMb5D6FzKpc2st2vjG3snpLyDvQ9o9C1zp9xqoVYoFCc03YF+mXjMKEbW4xD3wdbCB2+LQP1ts3XvhZdq440d1nf4koURowYoUpLS9W2bdvU5MmTYymY5dYS3fJjK/oHEWkPUDdYL3Q44GujDKXG8h6H/RoE6u+GL1bOcdzQehjX44hx7mEOXoN+6B7CRw1fitFhkJ+jReIltGg44Vt7dFPVTYZvvuv1UwevVyhrQ/AWSfVtCDqEexTUg0G2Owzq/9lcjg7o+VImx3CMuBGFxMREVV5errKzs1Xz5s3Vhg0bVM+ePaMtmH1+ox8edlXjrbC26IeNB/3jHugCnwB1CXosJrvPm4Ju+WVG/DZWa4+OK3/IqdClz3a4wL+B6A5j+0D1cYE/Zt4DH3Aq0duwaXJb47NfusDXSC3YszMJF9G3b1/Ky8vZuXMnAPPmzeOGG25gy5YtDnsWnDr0KIfxzDfooab/iu66f8BZd/w4NVP3fvT8Am7gK+BFw0CP6tvPsGJnXDqNzw0729gP/AiYhB4OYzN6tN/1hvmGXDFjiAs34SpRyMjIoKKiwv9/ZWUl/fr1O22b3NxcJkyYAEBKipNTa5y9uEUQhMYpN2yO0440ARRajD8DfoUel+gnDbYRUXCYvLw88vLyAPB4PA57IwhCU2A9cKPxdypwuWGd0DMsnk24ShSqqqro3Lmz///MzEyqqmKd80oQBME8atFT7C512hGLcNXQ2R6Ph+7du9OlSxeaN2/OuHHjWLx4sdNuCYIgNBlcVVM4efIkEydO5KOPPqJZs2a89tprbN682Wm3BEEQmgyuEgWApUuXsnTp2VoxEwRBcDeuCh8JgiAIziKiIAiCIPgRURAEQRD8iCgIgiAIfkQUBEEQBD8J6J7ccUltbS27d++Oev+UlBT2799vokfOcLaUA6QsbuRsKQdIWXxkZWWRmpoa8HPHR+xzytwyyqqUQ8riZjtbyiFlCc8kfCQIgiD4EVEQBEEQ/DRpUfjLX/7itAumcLaUA6QsbuRsKQdIWcIhrhPNgiAIgrk06ZqCIAiCcDoiCoIgCIKfJikKI0aMoLS0lG3btjF58mSn3YmI/Px8ampqKC4+NTtv+/btKSgooKysjIKCApKTk51zMEwyMzNZuXIlmzZtoqSkhIceegiIz7K0bNmSNWvWsGHDBkpKSnjyyScB6NKlC6tXr2bbtm3MmzeP5s2bO+toBCQmJlJYWMiSJUuA+C3Lzp072bhxI16v1z9TYzzeY+3ateNvf/sbW7ZsYfPmzfTv39/Scjje3tZOS0xMVOXl5So7O1s1b95cbdiwQfXs2dNxv8K1K664QuXk5Kji4mL/uueee05NnjxZAWry5Mnq2WefddzPUJaenq5ycnIUoNq2bau2bt2qevbsGZdlAVSbNm0UoJKSktTq1atVv3791DvvvKNuvfVWBaiZM2eq++67z3E/w7VHHnlEzZkzRy1ZskQBcVuWnTt3qo4dO562Lh7vsdmzZ6t77rlHAap58+aqXbt2VpbD+QLbaf3791fLli3z/z9lyhQ1ZcoUx/2KxLKysk4ThdLSUpWenq5AP2xLS0sd9zFSe++999SwYcPiviznnHOOWr9+verbt6/at2+fatasmYIz7zs3W0ZGhvr444/VVVdd5ReFeC1LY6IQb/fYeeedp3bs2HHGeqvK0eTCRxkZGVRUVPj/r6ysJCMjw0GPYictLY3q6moAqqurSUtLc9ijyMjKyiInJ4c1a9bEbVkSExPxer3U1tayfPlytm/fzsGDBzl58iQQX/fZiy++yGOPPUZdXR0AHTt2jNuyKKUoKChg3bp15ObmAvH3e8nOzmbfvn3MmjWLwsJC8vLyaN26tWXlaHKi0BRQSjntQti0adOGBQsW8PDDD3P48OEzPo+XstTV1ZGTk0NmZiZ9+/blu9/9rtMuRcW1115LbW0thYWFTrtiCoMGDeLyyy9n1KhRPPjgg1xxxRVnbOP2eywpKYnevXszc+ZMevfuzbfffsuUKVPO2M6scjQ5UaiqqqJz587+/zMzM6mqqnLQo9ipqakhPT0dgPT0dGprax32KDySkpJYsGABc+bMYdGiRUD8lsXHoUOHWLVqFT/84Q9JTk6mWbNmQPzcZwMHDuT6669n586dzJs3j6FDh/LSSy/FZVkA9uzZA8C+fftYtGgRffv2jbt7rLKyksrKStauXQvAu+++S+/evS0rR5MTBY/HQ/fu3enSpQvNmzdn3LhxLF682Gm3YmLx4sWMHz8egPHjx/P+++877FF45Ofns2XLFmbMmOFfF49lSUlJoV27dgC0atWKa665hi1btrBq1SrGjh0LxE9Zpk6dSufOncnOzmbcuHGsXLmSO+64Iy7L0rp1a9q2bev/e/jw4ZSUlMTdPVZTU0NFRQU9evQA4Oqrr2bz5s2WlsPxRIrdNmrUKLV161ZVXl6upk6d6rg/kdjcuXPVnj171LFjx1RFRYW6++67VYcOHdTHH3+sysrK1PLly1X79u0d9zOUDRw4UCmlVFFRkfJ6vcrr9apRo0bFZVkuvfRSVVhYqIqKilRxcbH6zW9+owCVnZ2t1qxZo7Zt26bmz5+vWrRo4bivkdiVV17pTzTHY1mys7PVhg0b1IYNG1RJSYn/tx6P99hll12mPB6PKioqUosWLVLJycmWlUOGuRAEQRD8NLnwkSAIghAYEQVBEATBj4iCIAiC4EdEQRAEQfAjoiAIgiD4EVEQBEEQ/IgoCALQoUMHvF4vXq+XvXv3UllZidfr5fDhw/zxj380/XyzZs1ix44d3HvvvQG3GTRoEJs2bTptmHRBsAPHO2aIibnJpk2bph599FFLzzFr1ix10003hdyu4Yi4YmJWm9QUBCEIV155pX+imWnTpjF79mz+8Y9/sGvXLsaMGcNzzz3Hxo0bWbp0KUlJSQD07t2bTz75hHXr1rFs2TL/+DTBGDt2LMXFxWzYsIFPP/3U0jIJQjBEFAQhArp168bQoUO5/vrreeutt1i1ahXf//73OXr0KNdeey1JSUn84Q9/YOzYsfzgBz/gtdde4+mnnw553CeeeIIRI0bQq1cvrr/+ehtKIgiNk+S0A4IQTyxdupQTJ05QXFxMs2bNWLZsGQDFxcV06dKFiy66iEsuuYTly5cD0KxZM/bu3RvyuJ9//jmzZ89m/vz5LFy40NIyCEIwRBQEIQL++9//AqCU4vjx4/71dXV1JCUlkZCQwKZNmxgwYEBEx73//vvp27cv1157LevXr+fyyy/nwIEDpvouCOEg4SNBMJGtW7dy/vnn079/f0DPGfG9730v5H5du3Zl7dq1TJs2jX379p0254cg2InUFATBRI4fP87YsWN5+eWXadeuHUlJSbz44ots3rw56H7Tp0+ne/fuJCQksGLFCoqKimzyWBDOxPEmUGJiTc2kSaqYW03CR4LgAIcOHeJ3v/tdyM5rS5YsYf/+/TZ6JjR1ZJIdQRAEwY/UFARBEAQ/IgqCIAiCHxEFQRAEwY+IgiAIguDn/wOxjNyivTVf9AAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "waypoints = [\n",
    "        [3, 3, np.pi/2],\n",
    "        [6, 6, 0],\n",
    "        [13.75, 12, np.pi/2],\n",
    "        [25, 24, 0],\n",
    "        [30, 30, np.pi/2],\n",
    "        [40, 38, 0],\n",
    "        [54, 50, np.pi/2],\n",
    "        [90, 90, 0],\n",
    "        [92, 90, np.pi/2],\n",
    "        [100, 100, 0]\n",
    "        ]\n",
    "R = np.array([[0.01,   0], [0, 0.01]])\n",
    "trajectory, controls, waypoints_reached, error = get_control_waypoints(\n",
    "    waypoints, R, dt=0.1, error_th=1, verbose=False)\n",
    "\n",
    "get_animation(waypoints, trajectory)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Current State = [0 0 0]\n",
      "Desired State = [0.    0.    0.796]\n",
      "State Error Magnitude = 0.7958959768960832\n",
      "Control Input = [0.    3.979]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [0.    0.    0.398]\n",
      "Desired State = [0.702 0.716 0.794]\n",
      "State Error Magnitude = 1.078638226756838\n",
      "Control Input = [4.625 1.981]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [0.426 0.179 0.596]\n",
      "Desired State = [1.406 1.43  0.789]\n",
      "State Error Magnitude = 1.6002064205736153\n",
      "Control Input = [7.564 0.964]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [1.052 0.604 0.692]\n",
      "Desired State = [2.114 2.136 0.78 ]\n",
      "State Error Magnitude = 1.8659485804721965\n",
      "Control Input = [8.976 0.438]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [1.743 1.177 0.736]\n",
      "Desired State = [2.826 2.833 0.768]\n",
      "State Error Magnitude = 1.97883163041754\n",
      "Control Input = [9.572 0.157]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [2.452 1.82  0.752]\n",
      "Desired State = [3.545 3.518 0.758]\n",
      "State Error Magnitude = 2.0190117184934877\n",
      "Control Input = [9.788 0.029]\n",
      "Current State = [3.167 2.488 0.755]\n",
      "Desired State = [3.545 3.518 0.758]\n",
      "State Error Magnitude = 1.0964284250332088\n",
      "Control Input = [4.901 0.015]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [3.524 2.824 0.756]\n",
      "Desired State = [4.264 4.201 0.765]\n",
      "State Error Magnitude = 1.5632349371125769\n",
      "Control Input = [7.415 0.044]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [4.064 3.333 0.761]\n",
      "Desired State = [4.975 4.9   0.79 ]\n",
      "State Error Magnitude = 1.8129895146027808\n",
      "Control Input = [8.703 0.146]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [4.694 3.933 0.775]\n",
      "Desired State = [5.671 5.63  0.832]\n",
      "State Error Magnitude = 1.9584020254014476\n",
      "Control Input = [9.426 0.281]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [5.367 4.593 0.803]\n",
      "Desired State = [6.342 6.407 0.886]\n",
      "State Error Magnitude = 2.060723874951587\n",
      "Control Input = [9.911 0.412]\n",
      "Current State = [6.055 5.306 0.845]\n",
      "Desired State = [6.342 6.407 0.886]\n",
      "State Error Magnitude = 1.1378545852100928\n",
      "Control Input = [5.066 0.206]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [6.392 5.685 0.865]\n",
      "Desired State = [6.985 7.238 0.938]\n",
      "State Error Magnitude = 1.6638436668792371\n",
      "Control Input = [7.834 0.364]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [6.9   6.282 0.902]\n",
      "Desired State = [7.6   8.122 0.986]\n",
      "State Error Magnitude = 1.9706148322349113\n",
      "Control Input = [9.389 0.424]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [7.482 7.018 0.944]\n",
      "Desired State = [8.188 9.055 1.031]\n",
      "State Error Magnitude = 2.157994278928339\n",
      "Control Input = [10.321  0.434]\n",
      "Current State = [8.087 7.854 0.987]\n",
      "Desired State = [8.188 9.055 1.031]\n",
      "State Error Magnitude = 1.2064888299727778\n",
      "Control Input = [5.291 0.217]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [8.379 8.296 1.009]\n",
      "Desired State = [ 8.749 10.037  1.072]\n",
      "State Error Magnitude = 1.7819003217048148\n",
      "Control Input = [8.357 0.314]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [8.824 9.003 1.041]\n",
      "Desired State = [ 9.283 11.065  1.11 ]\n",
      "State Error Magnitude = 2.1143234541519567\n",
      "Control Input = [10.059  0.346]\n",
      "Current State = [9.332 9.871 1.075]\n",
      "Desired State = [ 9.283 11.065  1.11 ]\n",
      "State Error Magnitude = 1.1962803265025754\n",
      "Control Input = [5.138 0.173]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [ 9.577 10.323  1.092]\n",
      "Desired State = [ 9.792 12.137  1.145]\n",
      "State Error Magnitude = 1.8281584075762722\n",
      "Control Input = [8.551 0.261]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [ 9.97  11.082  1.119]\n",
      "Desired State = [10.276 13.251  1.177]\n",
      "State Error Magnitude = 2.191370640071307\n",
      "Control Input = [10.423  0.291]\n",
      "Current State = [10.426 12.019  1.148]\n",
      "Desired State = [10.276 13.251  1.177]\n",
      "State Error Magnitude = 1.2410339172346323\n",
      "Control Input = [5.307 0.146]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [10.644 12.503  1.162]\n",
      "Desired State = [10.735 14.404  1.207]\n",
      "State Error Magnitude = 1.9036126188592224\n",
      "Control Input = [8.904 0.222]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [10.998 13.32   1.184]\n",
      "Desired State = [11.17  15.595  1.234]\n",
      "State Error Magnitude = 2.281582861866621\n",
      "Control Input = [10.859  0.249]\n",
      "Current State = [11.407 14.326  1.209]\n",
      "Desired State = [11.17  15.595  1.234]\n",
      "State Error Magnitude = 1.2907591525625732\n",
      "Control Input = [5.515 0.124]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [11.602 14.842  1.222]\n",
      "Desired State = [11.581 16.821  1.26 ]\n",
      "State Error Magnitude = 1.9793202138895425\n",
      "Control Input = [9.263 0.19 ]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [11.919 15.712  1.241]\n",
      "Desired State = [11.97  18.08   1.283]\n",
      "State Error Magnitude = 2.368626975949468\n",
      "Control Input = [11.282  0.214]\n",
      "Current State = [12.284 16.78   1.262]\n",
      "Desired State = [11.97  18.08   1.283]\n",
      "State Error Magnitude = 1.3381138375445665\n",
      "Control Input = [5.717 0.107]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [12.458 17.324  1.273]\n",
      "Desired State = [12.335 19.37   1.306]\n",
      "State Error Magnitude = 2.050019370650107\n",
      "Control Input = [9.599 0.164]\n",
      "Current State = [12.74  18.242  1.289]\n",
      "Desired State = [12.335 19.37   1.306]\n",
      "State Error Magnitude = 1.1989409231207742\n",
      "Control Input = [4.858 0.082]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [12.875 18.709  1.297]\n",
      "Desired State = [12.679 20.69   1.326]\n",
      "State Error Magnitude = 1.9909577337881652\n",
      "Control Input = [9.273 0.144]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [13.125 19.601  1.312]\n",
      "Desired State = [13.001 22.036  1.345]\n",
      "State Error Magnitude = 2.4377005826348714\n",
      "Control Input = [11.606  0.168]\n",
      "Current State = [13.423 20.723  1.329]\n",
      "Desired State = [13.001 22.036  1.345]\n",
      "State Error Magnitude = 1.3785791855488247\n",
      "Control Input = [5.865 0.084]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [13.563 21.293  1.337]\n",
      "Desired State = [13.302 23.406  1.363]\n",
      "State Error Magnitude = 2.1299830115700438\n",
      "Control Input = [9.979 0.132]\n",
      "Current State = [13.795 22.263  1.35 ]\n",
      "Desired State = [13.302 23.406  1.363]\n",
      "State Error Magnitude = 1.2446365955559249\n",
      "Control Input = [5.038 0.066]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [13.905 22.755  1.357]\n",
      "Desired State = [13.583 24.8    1.38 ]\n",
      "State Error Magnitude = 2.069984074255629\n",
      "Control Input = [9.648 0.118]\n",
      "Current State = [14.11  23.698  1.369]\n",
      "Desired State = [13.583 24.8    1.38 ]\n",
      "State Error Magnitude = 1.2213410712328274\n",
      "Control Input = [4.868 0.059]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [14.207 24.175  1.374]\n",
      "Desired State = [13.844 26.213  1.396]\n",
      "State Error Magnitude = 2.0709068250813307\n",
      "Control Input = [9.642 0.109]\n",
      "Current State = [14.395 25.12   1.385]\n",
      "Desired State = [13.844 26.213  1.396]\n",
      "State Error Magnitude = 1.2243781060549441\n",
      "Control Input = [4.862 0.054]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [14.485 25.598  1.391]\n",
      "Desired State = [14.085 27.645  1.411]\n",
      "State Error Magnitude = 2.085773607375314\n",
      "Control Input = [9.711 0.102]\n",
      "Current State = [14.659 26.554  1.401]\n",
      "Desired State = [14.085 27.645  1.411]\n",
      "State Error Magnitude = 1.2332975975545168\n",
      "Control Input = [4.894 0.051]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [14.742 27.036  1.406]\n",
      "Desired State = [14.307 29.093  1.425]\n",
      "State Error Magnitude = 2.102593710198135\n",
      "Control Input = [9.791 0.096]\n",
      "Current State = [14.902 28.002  1.416]\n",
      "Desired State = [14.307 29.093  1.425]\n",
      "State Error Magnitude = 1.242940996194153\n",
      "Control Input = [4.932 0.048]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [14.978 28.489  1.421]\n",
      "Desired State = [14.511 30.555  1.439]\n",
      "State Error Magnitude = 2.118265616326741\n",
      "Control Input = [9.865 0.091]\n",
      "Current State = [15.126 29.464  1.43 ]\n",
      "Desired State = [14.511 30.555  1.439]\n",
      "State Error Magnitude = 1.2519828605626597\n",
      "Control Input = [4.967 0.045]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [15.196 29.956  1.434]\n",
      "Desired State = [14.698 32.029  1.451]\n",
      "State Error Magnitude = 2.131961044533527\n",
      "Control Input = [9.928 0.086]\n",
      "Current State = [15.331 30.94   1.443]\n",
      "Desired State = [14.698 32.029  1.451]\n",
      "State Error Magnitude = 1.2600745138152623\n",
      "Control Input = [4.997 0.043]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [15.395 31.436  1.447]\n",
      "Desired State = [14.866 33.513  1.463]\n",
      "State Error Magnitude = 2.1434368870196074\n",
      "Control Input = [9.981 0.081]\n",
      "Current State = [15.518 32.426  1.455]\n",
      "Desired State = [14.866 33.513  1.463]\n",
      "State Error Magnitude = 1.2671184826407667\n",
      "Control Input = [5.022 0.041]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [15.576 32.925  1.459]\n",
      "Desired State = [15.019 35.004  1.475]\n",
      "State Error Magnitude = 2.1526035475786407\n",
      "Control Input = [10.021  0.077]\n",
      "Current State = [15.687 33.921  1.467]\n",
      "Desired State = [15.019 35.004  1.475]\n",
      "State Error Magnitude = 1.2730832224462463\n",
      "Control Input = [5.041 0.039]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [15.74  34.422  1.471]\n",
      "Desired State = [15.154 36.501  1.486]\n",
      "State Error Magnitude = 2.1594142764823285\n",
      "Control Input = [10.049  0.074]\n",
      "Current State = [15.84  35.422  1.478]\n",
      "Desired State = [15.154 36.501  1.486]\n",
      "State Error Magnitude = 1.2779556978358053\n",
      "Control Input = [5.054 0.037]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [15.886 35.925  1.482]\n",
      "Desired State = [15.275 38.001  1.496]\n",
      "State Error Magnitude = 2.163836581574922\n",
      "Control Input = [10.065  0.07 ]\n",
      "Current State = [15.976 36.928  1.489]\n",
      "Desired State = [15.275 38.001  1.496]\n",
      "State Error Magnitude = 1.2817291988271677\n",
      "Control Input = [5.06  0.035]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [16.017 37.432  1.492]\n",
      "Desired State = [15.38  39.502  1.506]\n",
      "State Error Magnitude = 2.1658446622556973\n",
      "Control Input = [10.068  0.067]\n",
      "Current State = [16.096 38.436  1.499]\n",
      "Desired State = [15.38  39.502  1.506]\n",
      "State Error Magnitude = 1.2844001798306248\n",
      "Control Input = [5.061 0.034]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [16.132 38.941  1.503]\n",
      "Desired State = [15.47  41.002  1.515]\n",
      "State Error Magnitude = 2.1654172636799203\n",
      "Control Input = [10.058  0.064]\n",
      "Current State = [16.201 39.944  1.509]\n",
      "Desired State = [15.47  41.002  1.515]\n",
      "State Error Magnitude = 1.285967424140575\n",
      "Control Input = [5.055 0.032]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [16.232 40.449  1.512]\n",
      "Desired State = [15.546 42.5    1.524]\n",
      "State Error Magnitude = 2.162536962120688\n",
      "Control Input = [10.036  0.062]\n",
      "Current State = [16.291 41.451  1.518]\n",
      "Desired State = [15.546 42.5    1.524]\n",
      "State Error Magnitude = 1.2864318228179072\n",
      "Control Input = [5.043 0.031]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [16.317 41.954  1.521]\n",
      "Desired State = [15.609 43.992  1.533]\n",
      "State Error Magnitude = 2.1571898599611163\n",
      "Control Input = [10.     0.059]\n",
      "Current State = [16.366 42.953  1.527]\n",
      "Desired State = [15.609 43.992  1.533]\n",
      "State Error Magnitude = 1.2857963307226463\n",
      "Control Input = [5.024 0.03 ]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [16.388 43.455  1.53 ]\n",
      "Desired State = [15.658 45.476  1.542]\n",
      "State Error Magnitude = 2.1493654276547103\n",
      "Control Input = [9.951 0.057]\n",
      "Current State = [16.429 44.449  1.536]\n",
      "Desired State = [15.658 45.476  1.542]\n",
      "State Error Magnitude = 1.2840659881082528\n",
      "Control Input = [4.999 0.029]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [16.446 44.949  1.539]\n",
      "Desired State = [15.695 46.952  1.55 ]\n",
      "State Error Magnitude = 2.1390564248497865\n",
      "Control Input = [9.889 0.055]\n",
      "Current State = [16.478 45.937  1.544]\n",
      "Desired State = [15.695 46.952  1.55 ]\n",
      "State Error Magnitude = 1.2812479797332854\n",
      "Control Input = [4.967 0.028]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [16.491 46.434  1.547]\n",
      "Desired State = [15.72  48.415  1.558]\n",
      "State Error Magnitude = 2.1262588837892746\n",
      "Control Input = [9.814 0.053]\n",
      "Current State = [16.514 47.415  1.552]\n",
      "Desired State = [15.72  48.415  1.558]\n",
      "State Error Magnitude = 1.2773517252053626\n",
      "Control Input = [4.929 0.027]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [16.523 47.907  1.555]\n",
      "Desired State = [15.733 49.865  1.565]\n",
      "State Error Magnitude = 2.1109721523623852\n",
      "Control Input = [9.725 0.052]\n",
      "Current State = [16.538 48.88   1.56 ]\n",
      "Desired State = [15.733 49.865  1.565]\n",
      "State Error Magnitude = 1.2723890002836884\n",
      "Control Input = [4.884 0.026]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [16.543 49.368  1.563]\n",
      "Desired State = [15.736 51.299  1.573]\n",
      "State Error Magnitude = 2.0931989992389894\n",
      "Control Input = [9.622 0.05 ]\n",
      "Current State = [16.551 50.33   1.568]\n",
      "Desired State = [15.736 51.299  1.573]\n",
      "State Error Magnitude = 1.2663740908853818\n",
      "Control Input = [4.832 0.025]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [16.553 50.814  1.57 ]\n",
      "Desired State = [15.727 52.715  1.58 ]\n",
      "State Error Magnitude = 2.072945786430472\n",
      "Control Input = [9.506 0.049]\n",
      "Current State = [16.553 51.764  1.575]\n",
      "Desired State = [15.727 52.715  1.58 ]\n",
      "State Error Magnitude = 1.2593239825752982\n",
      "Control Input = [4.773 0.024]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [16.551 52.242  1.578]\n",
      "Desired State = [15.709 54.111  1.587]\n",
      "State Error Magnitude = 2.0502227172833587\n",
      "Control Input = [9.377 0.048]\n",
      "Current State = [16.544 53.179  1.582]\n",
      "Desired State = [15.709 54.111  1.587]\n",
      "State Error Magnitude = 1.2512585891469754\n",
      "Control Input = [4.708 0.024]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [16.539 53.65   1.585]\n",
      "Desired State = [15.682 55.485  1.594]\n",
      "State Error Magnitude = 2.025044170916362\n",
      "Control Input = [9.233 0.047]\n",
      "Current State = [16.526 54.573  1.59 ]\n",
      "Desired State = [15.682 55.485  1.594]\n",
      "State Error Magnitude = 1.242201024731138\n",
      "Control Input = [4.636 0.023]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [16.517 55.037  1.592]\n",
      "Desired State = [15.646 56.834  1.601]\n",
      "State Error Magnitude = 1.9974291377510072\n",
      "Control Input = [9.076 0.046]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [16.498 55.944  1.597]\n",
      "Desired State = [15.601 58.157  1.608]\n",
      "State Error Magnitude = 2.3874813072248333\n",
      "Control Input = [11.174  0.057]\n",
      "Current State = [16.469 57.061  1.602]\n",
      "Desired State = [15.601 58.157  1.608]\n",
      "State Error Magnitude = 1.3978159766030491\n",
      "Control Input = [5.611 0.029]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [16.452 57.622  1.605]\n",
      "Desired State = [15.549 59.451  1.615]\n",
      "State Error Magnitude = 2.0395309214291126\n",
      "Control Input = [9.293 0.048]\n",
      "Current State = [16.42  58.551  1.61 ]\n",
      "Desired State = [15.549 59.451  1.615]\n",
      "State Error Magnitude = 1.2525461893710814\n",
      "Control Input = [4.667 0.024]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [16.402 59.017  1.612]\n",
      "Desired State = [15.489 60.714  1.621]\n",
      "State Error Magnitude = 1.9267980231431057\n",
      "Control Input = [8.667 0.046]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [16.366 59.883  1.617]\n",
      "Desired State = [15.422 61.944  1.628]\n",
      "State Error Magnitude = 2.2669041367211213\n",
      "Control Input = [10.513  0.057]\n",
      "Current State = [16.317 60.933  1.623]\n",
      "Desired State = [15.422 61.944  1.628]\n",
      "State Error Magnitude = 1.3502386010108423\n",
      "Control Input = [5.28  0.028]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [16.29  61.461  1.625]\n",
      "Desired State = [15.35  63.14   1.635]\n",
      "State Error Magnitude = 1.9244396489244628\n",
      "Control Input = [8.639 0.048]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [16.243 62.323  1.63 ]\n",
      "Desired State = [15.271 64.298  1.642]\n",
      "State Error Magnitude = 2.200621696538489\n",
      "Control Input = [10.143  0.059]\n",
      "Current State = [16.182 63.336  1.636]\n",
      "Desired State = [15.271 64.298  1.642]\n",
      "State Error Magnitude = 1.3251308869260767\n",
      "Control Input = [5.097 0.029]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [16.149 63.844  1.639]\n",
      "Desired State = [15.187 65.416  1.649]\n",
      "State Error Magnitude = 1.8429808795539409\n",
      "Control Input = [8.17 0.05]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [16.094 64.659  1.644]\n",
      "Desired State = [15.099 66.494  1.656]\n",
      "State Error Magnitude = 2.086507098883316\n",
      "Control Input = [9.51  0.061]\n",
      "Current State = [16.024 65.608  1.65 ]\n",
      "Desired State = [15.099 66.494  1.656]\n",
      "State Error Magnitude = 1.2806253466918067\n",
      "Control Input = [4.781 0.031]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [15.986 66.085  1.653]\n",
      "Desired State = [15.007 67.527  1.664]\n",
      "State Error Magnitude = 1.7438495457100185\n",
      "Control Input = [7.593 0.053]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [15.924 66.841  1.659]\n",
      "Desired State = [14.911 68.515  1.672]\n",
      "State Error Magnitude = 1.9567026372251377\n",
      "Control Input = [8.782 0.066]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [15.847 67.716  1.665]\n",
      "Desired State = [14.811 69.455  1.68 ]\n",
      "State Error Magnitude = 2.0241009594508723\n",
      "Control Input = [9.145 0.075]\n",
      "Current State = [15.76  68.626  1.673]\n",
      "Desired State = [14.811 69.455  1.68 ]\n",
      "State Error Magnitude = 1.2600338224576202\n",
      "Control Input = [4.605 0.038]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [15.714 69.085  1.676]\n",
      "Desired State = [14.71  70.345  1.689]\n",
      "State Error Magnitude = 1.6116840011663445\n",
      "Control Input = [6.798 0.064]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [15.642 69.761  1.683]\n",
      "Desired State = [14.606 71.183  1.699]\n",
      "State Error Magnitude = 1.759998680261805\n",
      "Control Input = [7.648 0.081]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [15.556 70.521  1.691]\n",
      "Desired State = [14.501 71.967  1.71 ]\n",
      "State Error Magnitude = 1.7907915576609859\n",
      "Control Input = [7.812 0.095]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [15.463 71.296  1.7  ]\n",
      "Desired State = [14.394 72.694  1.722]\n",
      "State Error Magnitude = 1.7596467038652472\n",
      "Control Input = [7.622 0.109]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [15.364 72.052  1.711]\n",
      "Desired State = [14.288 73.363  1.736]\n",
      "State Error Magnitude = 1.6965068461503812\n",
      "Control Input = [7.244 0.125]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [15.263 72.769  1.724]\n",
      "Desired State = [14.181 73.971  1.753]\n",
      "State Error Magnitude = 1.6171291679843214\n",
      "Control Input = [6.763 0.146]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [15.16  73.438  1.738]\n",
      "Desired State = [14.075 74.516  1.774]\n",
      "State Error Magnitude = 1.5300266754274763\n",
      "Control Input = [6.222 0.176]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [15.056 74.051  1.756]\n",
      "Desired State = [13.97  74.997  1.8  ]\n",
      "State Error Magnitude = 1.4402247107309543\n",
      "Control Input = [5.646 0.218]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [14.952 74.606  1.778]\n",
      "Desired State = [13.867 75.41   1.834]\n",
      "State Error Magnitude = 1.3512981649934177\n",
      "Control Input = [5.048 0.282]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [14.848 75.1    1.806]\n",
      "Desired State = [13.766 75.754  1.883]\n",
      "State Error Magnitude = 1.266626917519653\n",
      "Control Input = [4.44  0.386]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [14.745 75.532  1.845]\n",
      "Desired State = [13.668 76.027  1.959]\n",
      "State Error Magnitude = 1.1906904318846618\n",
      "Control Input = [3.838 0.574]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [14.641 75.901  1.902]\n",
      "Desired State = [13.573 76.226  2.094]\n",
      "State Error Magnitude = 1.132742038988792\n",
      "Control Input = [3.271 0.958]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [14.535 76.211  1.998]\n",
      "Desired State = [13.482 76.349  2.38 ]\n",
      "State Error Magnitude = 1.128738376161858\n",
      "Control Input = [2.813 1.909]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [14.418 76.467  2.189]\n",
      "Desired State = [13.395 76.395  3.067]\n",
      "State Error Magnitude = 1.3505259387462234\n",
      "Control Input = [2.675 4.391]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [14.263 76.685  2.628]\n",
      "Desired State = [13.313 76.361 -2.389]\n",
      "State Error Magnitude = 5.115775527995709\n",
      "Control Input = [  3.346 -25.081]\n",
      "Current State = [13.972 76.849  0.12 ]\n",
      "Desired State = [13.313 76.361 -2.389]\n",
      "State Error Magnitude = 2.6388147315985577\n",
      "Control Input = [ -3.565 -12.541]\n",
      "Current State = [13.618 76.807 -1.134]\n",
      "Desired State = [13.313 76.361 -2.389]\n",
      "State Error Magnitude = 1.3653371140500468\n",
      "Control Input = [ 1.371 -6.27 ]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [13.676 76.682 -1.762]\n",
      "Desired State = [13.236 76.246 -2.009]\n",
      "State Error Magnitude = 0.6679172705808304\n",
      "Control Input = [ 2.562 -1.24 ]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [13.627 76.431 -1.885]\n",
      "Desired State = [13.165 76.045 -1.843]\n",
      "State Error Magnitude = 0.6036188923929531\n",
      "Control Input = [2.548 0.212]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [13.549 76.188 -1.864]\n",
      "Desired State = [13.1   75.759 -1.754]\n",
      "State Error Magnitude = 0.6305309469325914\n",
      "Control Input = [2.704 0.552]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [13.47  75.93  -1.809]\n",
      "Desired State = [13.043 75.384 -1.699]\n",
      "State Error Magnitude = 0.7018041211219785\n",
      "Control Input = [3.154 0.552]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [13.396 75.623 -1.754]\n",
      "Desired State = [12.992 74.919 -1.661]\n",
      "State Error Magnitude = 0.8167489220300667\n",
      "Control Input = [3.829 0.464]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [13.326 75.247 -1.707]\n",
      "Desired State = [12.95  74.363 -1.634]\n",
      "State Error Magnitude = 0.9632877760945863\n",
      "Control Input = [4.634 0.365]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [13.263 74.788 -1.671]\n",
      "Desired State = [12.916 73.719 -1.615]\n",
      "State Error Magnitude = 1.1247992907243152\n",
      "Control Input = [5.489 0.281]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [13.208 74.241 -1.643]\n",
      "Desired State = [12.89  72.992 -1.599]\n",
      "State Error Magnitude = 1.2897490362988568\n",
      "Control Input = [6.344 0.218]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [13.163 73.609 -1.621]\n",
      "Desired State = [12.872 72.187 -1.587]\n",
      "State Error Magnitude = 1.451827735338127\n",
      "Control Input = [7.175 0.172]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [13.127 72.892 -1.604]\n",
      "Desired State = [12.863 71.306 -1.576]\n",
      "State Error Magnitude = 1.6079263559175008\n",
      "Control Input = [7.969 0.139]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [13.1   72.096 -1.59 ]\n",
      "Desired State = [12.863 70.355 -1.567]\n",
      "State Error Magnitude = 1.7566094467203748\n",
      "Control Input = [8.723 0.116]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [13.084 71.224 -1.578]\n",
      "Desired State = [12.871 69.338 -1.558]\n",
      "State Error Magnitude = 1.8972518557467097\n",
      "Control Input = [9.434 0.099]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [13.076 70.28  -1.568]\n",
      "Desired State = [12.889 68.259 -1.551]\n",
      "State Error Magnitude = 2.029600716620824\n",
      "Control Input = [10.102  0.087]\n",
      "Current State = [13.079 69.27  -1.56 ]\n",
      "Desired State = [12.889 68.259 -1.551]\n",
      "State Error Magnitude = 1.0283917512909866\n",
      "Control Input = [5.042 0.044]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [13.084 68.766 -1.555]\n",
      "Desired State = [12.915 67.123 -1.544]\n",
      "State Error Magnitude = 1.651801627775083\n",
      "Control Input = [8.201 0.057]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [13.097 67.946 -1.55 ]\n",
      "Desired State = [12.951 65.933 -1.537]\n",
      "State Error Magnitude = 2.0184598782609275\n",
      "Control Input = [10.048  0.061]\n",
      "Current State = [13.118 66.941 -1.544]\n",
      "Desired State = [12.951 65.933 -1.537]\n",
      "State Error Magnitude = 1.0223265926795804\n",
      "Control Input = [5.018 0.031]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [13.132 66.44  -1.54 ]\n",
      "Desired State = [12.997 64.693 -1.531]\n",
      "State Error Magnitude = 1.7515019778621583\n",
      "Control Input = [8.707 0.047]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [13.158 65.569 -1.536]\n",
      "Desired State = [13.052 63.409 -1.525]\n",
      "State Error Magnitude = 2.162902366634369\n",
      "Control Input = [10.776  0.054]\n",
      "Current State = [13.196 64.492 -1.53 ]\n",
      "Desired State = [13.052 63.409 -1.525]\n",
      "State Error Magnitude = 1.0929252221275554\n",
      "Control Input = [5.383 0.027]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [13.218 63.954 -1.528]\n",
      "Desired State = [13.116 62.084 -1.519]\n",
      "State Error Magnitude = 1.8732098097706793\n",
      "Control Input = [9.322 0.043]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [13.258 63.023 -1.523]\n",
      "Desired State = [13.191 60.723 -1.513]\n",
      "State Error Magnitude = 2.301590977668435\n",
      "Control Input = [11.474  0.051]\n",
      "Current State = [13.312 61.877 -1.518]\n",
      "Desired State = [13.191 60.723 -1.513]\n",
      "State Error Magnitude = 1.1608606003965627\n",
      "Control Input = [5.732 0.026]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [13.342 61.305 -1.516]\n",
      "Desired State = [13.275 59.329 -1.507]\n",
      "State Error Magnitude = 1.97684986671655\n",
      "Control Input = [9.845 0.043]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [13.397 60.322 -1.511]\n",
      "Desired State = [13.37  57.907 -1.501]\n",
      "State Error Magnitude = 2.414521118310865\n",
      "Control Input = [12.043  0.051]\n",
      "Current State = [13.468 59.119 -1.506]\n",
      "Desired State = [13.37  57.907 -1.501]\n",
      "State Error Magnitude = 1.216162948772718\n",
      "Control Input = [6.017 0.026]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [13.507 58.519 -1.504]\n",
      "Desired State = [13.475 56.462 -1.495]\n",
      "State Error Magnitude = 2.057434797458017\n",
      "Control Input = [10.252  0.043]\n",
      "Current State = [13.576 57.496 -1.499]\n",
      "Desired State = [13.475 56.462 -1.495]\n",
      "State Error Magnitude = 1.0390991259347753\n",
      "Control Input = [5.122 0.022]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [13.612 56.985 -1.497]\n",
      "Desired State = [13.591 54.997 -1.489]\n",
      "State Error Magnitude = 1.9883536972865135\n",
      "Control Input = [9.907 0.042]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [13.685 55.997 -1.493]\n",
      "Desired State = [13.717 53.517 -1.482]\n",
      "State Error Magnitude = 2.4806455910289715\n",
      "Control Input = [12.377  0.053]\n",
      "Current State = [13.781 54.763 -1.488]\n",
      "Desired State = [13.717 53.517 -1.482]\n",
      "State Error Magnitude = 1.248049320082291\n",
      "Control Input = [6.184 0.027]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [13.832 54.147 -1.485]\n",
      "Desired State = [13.855 52.026 -1.476]\n",
      "State Error Magnitude = 2.1214382459085552\n",
      "Control Input = [10.577  0.047]\n",
      "Current State = [13.923 53.093 -1.48 ]\n",
      "Desired State = [13.855 52.026 -1.476]\n",
      "State Error Magnitude = 1.0696612152873397\n",
      "Control Input = [5.285 0.023]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [13.971 52.567 -1.478]\n",
      "Desired State = [14.003 50.528 -1.469]\n",
      "State Error Magnitude = 2.039371034550838\n",
      "Control Input = [10.167  0.047]\n",
      "Current State = [14.065 51.554 -1.473]\n",
      "Desired State = [14.003 50.528 -1.469]\n",
      "State Error Magnitude = 1.0286884857151317\n",
      "Control Input = [5.08  0.023]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [14.114 51.049 -1.471]\n",
      "Desired State = [14.162 49.027 -1.461]\n",
      "State Error Magnitude = 2.02231544030743\n",
      "Control Input = [10.082  0.048]\n",
      "Current State = [14.215 50.046 -1.466]\n",
      "Desired State = [14.162 49.027 -1.461]\n",
      "State Error Magnitude = 1.0198830374833743\n",
      "Control Input = [5.037 0.024]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [14.267 49.545 -1.464]\n",
      "Desired State = [14.333 47.528 -1.454]\n",
      "State Error Magnitude = 2.0173669480643754\n",
      "Control Input = [10.059  0.051]\n",
      "Current State = [14.375 48.545 -1.459]\n",
      "Desired State = [14.333 47.528 -1.454]\n",
      "State Error Magnitude = 1.017054363247679\n",
      "Control Input = [5.025 0.025]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [14.431 48.045 -1.456]\n",
      "Desired State = [14.515 46.036 -1.445]\n",
      "State Error Magnitude = 2.0113319957332236\n",
      "Control Input = [10.03   0.054]\n",
      "Current State = [14.546 47.049 -1.451]\n",
      "Desired State = [14.515 46.036 -1.445]\n",
      "State Error Magnitude = 1.0136705878484091\n",
      "Control Input = [5.011 0.027]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [14.606 46.551 -1.448]\n",
      "Desired State = [14.708 44.553 -1.437]\n",
      "State Error Magnitude = 2.0009312162988153\n",
      "Control Input = [9.979 0.057]\n",
      "Current State = [14.728 45.561 -1.442]\n",
      "Desired State = [14.708 44.553 -1.437]\n",
      "State Error Magnitude = 1.0081052406327349\n",
      "Control Input = [4.985 0.029]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [14.792 45.067 -1.439]\n",
      "Desired State = [14.913 43.085 -1.427]\n",
      "State Error Magnitude = 1.9853634146316885\n",
      "Control Input = [9.902 0.062]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [14.921 44.085 -1.433]\n",
      "Desired State = [15.13  41.636 -1.417]\n",
      "State Error Magnitude = 2.458284370142405\n",
      "Control Input = [12.274  0.082]\n",
      "Current State = [15.09  42.869 -1.425]\n",
      "Desired State = [15.13  41.636 -1.417]\n",
      "State Error Magnitude = 1.234190673246705\n",
      "Control Input = [6.132 0.041]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [15.179 42.262 -1.421]\n",
      "Desired State = [15.36  40.209 -1.406]\n",
      "State Error Magnitude = 2.0613097826448104\n",
      "Control Input = [10.287  0.076]\n",
      "Current State = [15.332 41.245 -1.413]\n",
      "Desired State = [15.36  40.209 -1.406]\n",
      "State Error Magnitude = 1.0365578016848707\n",
      "Control Input = [5.138 0.038]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [15.413 40.738 -1.41 ]\n",
      "Desired State = [15.601 38.81  -1.394]\n",
      "State Error Magnitude = 1.9372153326379098\n",
      "Control Input = [9.666 0.079]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [15.568 39.784 -1.402]\n",
      "Desired State = [15.855 37.442 -1.381]\n",
      "State Error Magnitude = 2.359368556085139\n",
      "Control Input = [11.783  0.105]\n",
      "Current State = [15.766 38.622 -1.391]\n",
      "Desired State = [15.855 37.442 -1.381]\n",
      "State Error Magnitude = 1.183606337981635\n",
      "Control Input = [5.885 0.053]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [15.871 38.043 -1.386]\n",
      "Desired State = [16.121 36.11  -1.366]\n",
      "State Error Magnitude = 1.9495137015188715\n",
      "Control Input = [9.732 0.099]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [16.05  37.086 -1.376]\n",
      "Desired State = [16.4   34.817 -1.35 ]\n",
      "State Error Magnitude = 2.2959929398690866\n",
      "Control Input = [11.469  0.13 ]\n",
      "Current State = [16.272 35.961 -1.363]\n",
      "Desired State = [16.4   34.817 -1.35 ]\n",
      "State Error Magnitude = 1.1510022308661156\n",
      "Control Input = [5.728 0.065]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [16.39  35.401 -1.357]\n",
      "Desired State = [16.691 33.569 -1.332]\n",
      "State Error Magnitude = 1.8562435572818339\n",
      "Control Input = [9.268 0.123]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [16.587 34.495 -1.344]\n",
      "Desired State = [16.996 32.37  -1.312]\n",
      "State Error Magnitude = 2.164756158095602\n",
      "Control Input = [10.815  0.163]\n",
      "Current State = [16.83  33.441 -1.328]\n",
      "Desired State = [16.996 32.37  -1.312]\n",
      "State Error Magnitude = 1.0845385417395936\n",
      "Control Input = [5.401 0.081]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [16.96  32.917 -1.32 ]\n",
      "Desired State = [17.314 31.223 -1.289]\n",
      "State Error Magnitude = 1.7313233281878073\n",
      "Control Input = [8.646 0.155]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [17.175 32.079 -1.304]\n",
      "Desired State = [17.645 30.132 -1.263]\n",
      "State Error Magnitude = 2.003492191651854\n",
      "Control Input = [10.011  0.209]\n",
      "Current State = [17.438 31.114 -1.283]\n",
      "Desired State = [17.645 30.132 -1.263]\n",
      "State Error Magnitude = 1.0030585749483962\n",
      "Control Input = [4.998 0.105]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [17.58  30.634 -1.273]\n",
      "Desired State = [17.989 29.103 -1.232]\n",
      "State Error Magnitude = 1.5853374320360063\n",
      "Control Input = [7.919 0.204]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [17.812 29.877 -1.253]\n",
      "Desired State = [18.347 28.14  -1.197]\n",
      "State Error Magnitude = 1.8190017501425257\n",
      "Control Input = [9.089 0.279]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [18.097 29.014 -1.225]\n",
      "Desired State = [18.719 27.246 -1.155]\n",
      "State Error Magnitude = 1.8759947562001704\n",
      "Control Input = [9.373 0.348]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [18.415 28.132 -1.19 ]\n",
      "Desired State = [19.104 26.425 -1.106]\n",
      "State Error Magnitude = 1.842894131042494\n",
      "Control Input = [9.205 0.422]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [18.757 27.278 -1.148]\n",
      "Desired State = [19.504 25.683 -1.046]\n",
      "State Error Magnitude = 1.763724580800041\n",
      "Control Input = [8.803 0.511]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [19.118 26.475 -1.097]\n",
      "Desired State = [19.917 25.024 -0.972]\n",
      "State Error Magnitude = 1.661668517249331\n",
      "Control Input = [8.282 0.622]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [19.496 25.738 -1.035]\n",
      "Desired State = [20.345 24.45  -0.882]\n",
      "State Error Magnitude = 1.5501199153028722\n",
      "Control Input = [7.705 0.763]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [19.89  25.076 -0.958]\n",
      "Desired State = [20.788 23.968 -0.769]\n",
      "State Error Magnitude = 1.4385012575438074\n",
      "Control Input = [7.113 0.945]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [20.299 24.494 -0.864]\n",
      "Desired State = [21.245 23.581 -0.629]\n",
      "State Error Magnitude = 1.335457789014998\n",
      "Control Input = [6.543 1.171]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [20.724 23.997 -0.747]\n",
      "Desired State = [21.717 23.293 -0.459]\n",
      "State Error Magnitude = 1.2502982863892138\n",
      "Control Input = [6.032 1.439]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [21.167 23.587 -0.603]\n",
      "Desired State = [22.204 23.109 -0.259]\n",
      "State Error Magnitude = 1.1922649531790097\n",
      "Control Input = [5.626 1.717]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [21.63  23.268 -0.431]\n",
      "Desired State = [22.705 23.032 -0.042]\n",
      "State Error Magnitude = 1.1676345877935597\n",
      "Control Input = [5.377 1.947]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [22.119 23.043 -0.236]\n",
      "Desired State = [23.223 23.068  0.175]\n",
      "State Error Magnitude = 1.1783705632690404\n",
      "Control Input = [5.337 2.058]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [22.638 22.918 -0.03 ]\n",
      "Desired State = [23.755 23.22   0.373]\n",
      "State Error Magnitude = 1.225684361463974\n",
      "Control Input = [5.539 2.017]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [23.191 22.902  0.171]\n",
      "Desired State = [24.303 23.492  0.541]\n",
      "State Error Magnitude = 1.3122077379572292\n",
      "Control Input = [5.981 1.849]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [23.781 23.004  0.356]\n",
      "Desired State = [24.867 23.889  0.679]\n",
      "State Error Magnitude = 1.4382567406388245\n",
      "Control Input = [6.635 1.612]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [24.402 23.235  0.517]\n",
      "Desired State = [25.446 24.414  0.783]\n",
      "State Error Magnitude = 1.5966936521846462\n",
      "Control Input = [7.452 1.325]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [25.05  23.604  0.65 ]\n",
      "Desired State = [26.042 25.05   0.849]\n",
      "State Error Magnitude = 1.7654660442848733\n",
      "Control Input = [8.327 0.993]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [25.713 24.108  0.749]\n",
      "Desired State = [26.654 25.777  0.889]\n",
      "State Error Magnitude = 1.9216729237904908\n",
      "Control Input = [9.132 0.698]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [26.382 24.73   0.819]\n",
      "Desired State = [27.283 26.571  0.91 ]\n",
      "State Error Magnitude = 2.0522675500930756\n",
      "Control Input = [9.804 0.456]\n",
      "Current State = [27.051 25.446  0.865]\n",
      "Desired State = [27.283 26.571  0.91 ]\n",
      "State Error Magnitude = 1.1498021405630803\n",
      "Control Input = [5.033 0.228]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [27.378 25.829  0.887]\n",
      "Desired State = [27.929 27.41   0.917]\n",
      "State Error Magnitude = 1.6742672709062298\n",
      "Control Input = [7.868 0.146]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [27.874 26.439  0.902]\n",
      "Desired State = [28.591 28.27   0.91 ]\n",
      "State Error Magnitude = 1.9663275616269413\n",
      "Control Input = [9.405 0.039]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [28.458 27.177  0.906]\n",
      "Desired State = [29.272 29.129  0.89 ]\n",
      "State Error Magnitude = 2.1155218447149178\n",
      "Control Input = [10.195 -0.078]\n",
      "Current State = [29.087 27.979  0.898]\n",
      "Desired State = [29.272 29.129  0.89 ]\n",
      "State Error Magnitude = 1.1649846882412422\n",
      "Control Input = [ 5.075 -0.039]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [29.403 28.376  0.894]\n",
      "Desired State = [29.97  29.965  0.857]\n",
      "State Error Magnitude = 1.6877517434361993\n",
      "Control Input = [ 7.971 -0.185]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [29.902 28.998  0.876]\n",
      "Desired State = [30.686 30.759  0.817]\n",
      "State Error Magnitude = 1.9288472949124795\n",
      "Control Input = [ 9.274 -0.295]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [30.496 29.71   0.846]\n",
      "Desired State = [31.418 31.51   0.779]\n",
      "State Error Magnitude = 2.0233926615836606\n",
      "Control Input = [ 9.795 -0.338]\n",
      "Current State = [31.145 30.444  0.812]\n",
      "Desired State = [31.418 31.51   0.779]\n",
      "State Error Magnitude = 1.1011079254332334\n",
      "Control Input = [ 4.81  -0.169]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [31.476 30.793  0.795]\n",
      "Desired State = [32.166 32.221  0.743]\n",
      "State Error Magnitude = 1.5871332592686633\n",
      "Control Input = [ 7.516 -0.262]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [32.002 31.329  0.769]\n",
      "Desired State = [32.927 32.897  0.711]\n",
      "State Error Magnitude = 1.8213103731159301\n",
      "Control Input = [ 8.776 -0.294]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [32.632 31.94   0.74 ]\n",
      "Desired State = [33.7   33.543  0.681]\n",
      "State Error Magnitude = 1.9265248318719825\n",
      "Control Input = [ 9.345 -0.292]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [33.322 32.57   0.711]\n",
      "Desired State = [34.483 34.161  0.656]\n",
      "State Error Magnitude = 1.970163906202638\n",
      "Control Input = [ 9.588 -0.273]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [34.049 33.195  0.683]\n",
      "Desired State = [35.275 34.757  0.635]\n",
      "State Error Magnitude = 1.985688415297335\n",
      "Control Input = [ 9.682 -0.244]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [34.8   33.807  0.659]\n",
      "Desired State = [36.074 35.334  0.617]\n",
      "State Error Magnitude = 1.9893044989859183\n",
      "Control Input = [ 9.712 -0.209]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [35.568 34.401  0.638]\n",
      "Desired State = [36.879 35.896  0.604]\n",
      "State Error Magnitude = 1.988712179653793\n",
      "Control Input = [ 9.718 -0.171]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [36.348 34.98   0.621]\n",
      "Desired State = [37.688 36.448  0.595]\n",
      "State Error Magnitude = 1.987481376061227\n",
      "Control Input = [ 9.717 -0.131]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [37.139 35.545  0.608]\n",
      "Desired State = [38.499 36.994  0.59 ]\n",
      "State Error Magnitude = 1.9872145215220882\n",
      "Control Input = [ 9.719 -0.089]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [37.937 36.1    0.599]\n",
      "Desired State = [39.311 37.538  0.59 ]\n",
      "State Error Magnitude = 1.9886108998592358\n",
      "Control Input = [ 9.727 -0.046]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [38.74  36.649  0.594]\n",
      "Desired State = [40.123 38.083  0.594]\n",
      "State Error Magnitude = 1.9919880976790663\n",
      "Control Input = [ 9.743 -0.003]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [39.547 37.194  0.594]\n",
      "Desired State = [40.932 38.633  0.6  ]\n",
      "State Error Magnitude = 1.9971331187374317\n",
      "Control Input = [9.766 0.03 ]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [40.356 37.741  0.597]\n",
      "Desired State = [41.739 39.19   0.608]\n",
      "State Error Magnitude = 2.002898175484364\n",
      "Control Input = [9.791 0.053]\n",
      "Current State = [41.166 38.292  0.602]\n",
      "Desired State = [41.739 39.19   0.608]\n",
      "State Error Magnitude = 1.065518008915829\n",
      "Control Input = [4.907 0.026]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [41.57  38.57   0.605]\n",
      "Desired State = [42.543 39.754  0.616]\n",
      "State Error Magnitude = 1.5326215071760763\n",
      "Control Input = [7.369 0.056]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [42.176 38.989  0.611]\n",
      "Desired State = [43.343 40.327  0.626]\n",
      "State Error Magnitude = 1.7750186026190227\n",
      "Control Input = [8.615 0.077]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [42.882 39.483  0.618]\n",
      "Desired State = [44.139 40.908  0.637]\n",
      "State Error Magnitude = 1.9003038158355279\n",
      "Control Input = [9.251 0.093]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [43.636 40.019  0.628]\n",
      "Desired State = [44.929 41.501  0.649]\n",
      "State Error Magnitude = 1.9665218530402797\n",
      "Control Input = [9.584 0.106]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [44.412 40.582  0.638]\n",
      "Desired State = [45.714 42.104  0.662]\n",
      "State Error Magnitude = 2.003320228913618\n",
      "Control Input = [9.765 0.119]\n",
      "Current State = [45.196 41.164  0.65 ]\n",
      "Desired State = [45.714 42.104  0.662]\n",
      "State Error Magnitude = 1.073519496771604\n",
      "Control Input = [4.908 0.059]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [45.586 41.461  0.656]\n",
      "Desired State = [46.493 42.72   0.676]\n",
      "State Error Magnitude = 1.5511453118457956\n",
      "Control Input = [7.43 0.1 ]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [46.175 41.915  0.666]\n",
      "Desired State = [47.265 43.349  0.691]\n",
      "State Error Magnitude = 1.8013805706488732\n",
      "Control Input = [8.715 0.126]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [46.86  42.453  0.679]\n",
      "Desired State = [48.029 43.992  0.708]\n",
      "State Error Magnitude = 1.9327151662553037\n",
      "Control Input = [9.38  0.144]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [47.59  43.042  0.693]\n",
      "Desired State = [48.786 44.651  0.725]\n",
      "State Error Magnitude = 2.004143320727527\n",
      "Control Input = [9.736 0.158]\n",
      "Current State = [48.339 43.664  0.709]\n",
      "Desired State = [48.786 44.651  0.725]\n",
      "State Error Magnitude = 1.082655633727354\n",
      "Control Input = [4.905 0.079]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [48.711 43.984  0.717]\n",
      "Desired State = [49.533 45.325  0.743]\n",
      "State Error Magnitude = 1.5734708571177183\n",
      "Control Input = [7.506 0.131]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [49.277 44.477  0.73 ]\n",
      "Desired State = [50.272 46.017  0.762]\n",
      "State Error Magnitude = 1.8336815339593706\n",
      "Control Input = [8.842 0.161]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [49.936 45.067  0.746]\n",
      "Desired State = [51.001 46.727  0.782]\n",
      "State Error Magnitude = 1.9727021189310165\n",
      "Control Input = [9.545 0.181]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [50.637 45.715  0.764]\n",
      "Desired State = [51.719 47.456  0.803]\n",
      "State Error Magnitude = 2.050681455011179\n",
      "Control Input = [9.932 0.195]\n",
      "Current State = [51.354 46.402  0.784]\n",
      "Desired State = [51.719 47.456  0.803]\n",
      "State Error Magnitude = 1.1157352687833972\n",
      "Control Input = [5.015 0.097]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [51.709 46.756  0.794]\n",
      "Desired State = [52.426 48.205  0.825]\n",
      "State Error Magnitude = 1.617418627473403\n",
      "Control Input = [7.682 0.157]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [52.248 47.304  0.809]\n",
      "Desired State = [53.122 48.975  0.847]\n",
      "State Error Magnitude = 1.8871795134023992\n",
      "Control Input = [9.068 0.191]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [52.873 47.96   0.828]\n",
      "Desired State = [53.806 49.768  0.871]\n",
      "State Error Magnitude = 2.0345569482061134\n",
      "Control Input = [9.812 0.211]\n",
      "Current State = [53.537 48.683  0.849]\n",
      "Desired State = [53.806 49.768  0.871]\n",
      "State Error Magnitude = 1.1178865890506462\n",
      "Control Input = [4.961 0.105]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [53.864 49.056  0.86 ]\n",
      "Desired State = [54.476 50.583  0.894]\n",
      "State Error Magnitude = 1.6458942015342115\n",
      "Control Input = [7.785 0.168]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [54.372 49.645  0.877]\n",
      "Desired State = [55.135 51.42   0.915]\n",
      "State Error Magnitude = 1.9321906384698857\n",
      "Control Input = [9.261 0.191]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [54.964 50.357  0.896]\n",
      "Desired State = [55.781 52.279  0.935]\n",
      "State Error Magnitude = 2.0881159543038477\n",
      "Control Input = [10.053  0.194]\n",
      "Current State = [55.593 51.142  0.915]\n",
      "Desired State = [55.781 52.279  0.935]\n",
      "State Error Magnitude = 1.1520876941127\n",
      "Control Input = [5.08  0.097]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [55.902 51.545  0.925]\n",
      "Desired State = [56.417 53.156  0.953]\n",
      "State Error Magnitude = 1.6917489218074921\n",
      "Control Input = [7.984 0.139]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [56.382 52.183  0.939]\n",
      "Desired State = [57.042 54.052  0.969]\n",
      "State Error Magnitude = 1.9825023215538213\n",
      "Control Input = [9.49  0.152]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [56.943 52.949  0.954]\n",
      "Desired State = [57.658 54.964  0.985]\n",
      "State Error Magnitude = 2.138823801609765\n",
      "Control Input = [10.289  0.151]\n",
      "Current State = [57.538 53.788  0.969]\n",
      "Desired State = [57.658 54.964  0.985]\n",
      "State Error Magnitude = 1.182300022289362\n",
      "Control Input = [5.188 0.076]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [57.831 54.216  0.977]\n",
      "Desired State = [58.265 55.892  0.998]\n",
      "State Error Magnitude = 1.7308262168096198\n",
      "Control Input = [8.156 0.106]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [58.288 54.892  0.988]\n",
      "Desired State = [58.863 56.833  1.01 ]\n",
      "State Error Magnitude = 2.0242624142972203\n",
      "Control Input = [9.683 0.114]\n",
      "Current State = [58.821 55.7    0.999]\n",
      "Desired State = [58.863 56.833  1.01 ]\n",
      "State Error Magnitude = 1.133276622555426\n",
      "Control Input = [4.875 0.057]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [59.085 56.11   1.005]\n",
      "Desired State = [59.454 57.786  1.021]\n",
      "State Error Magnitude = 1.7159888345984604\n",
      "Control Input = [8.061 0.082]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [59.517 56.79   1.013]\n",
      "Desired State = [60.038 58.75   1.03 ]\n",
      "State Error Magnitude = 2.0275514264102608\n",
      "Control Input = [9.69  0.089]\n",
      "Current State = [60.031 57.612  1.022]\n",
      "Desired State = [60.038 58.75   1.03 ]\n",
      "State Error Magnitude = 1.1374173008653474\n",
      "Control Input = [4.871 0.044]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [60.285 58.028  1.026]\n",
      "Desired State = [60.617 59.723  1.039]\n",
      "State Error Magnitude = 1.727381416373848\n",
      "Control Input = [8.109 0.063]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [60.705 58.721  1.032]\n",
      "Desired State = [61.19  60.704  1.046]\n",
      "State Error Magnitude = 2.0412210469266157\n",
      "Control Input = [9.754 0.066]\n",
      "Current State = [61.205 59.559  1.039]\n",
      "Desired State = [61.19  60.704  1.046]\n",
      "State Error Magnitude = 1.1455241401985288\n",
      "Control Input = [4.897 0.033]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [61.453 59.981  1.042]\n",
      "Desired State = [61.758 61.692  1.051]\n",
      "State Error Magnitude = 1.7379041879695953\n",
      "Control Input = [8.156 0.045]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [61.865 60.685  1.047]\n",
      "Desired State = [62.322 62.684  1.056]\n",
      "State Error Magnitude = 2.0511102039974114\n",
      "Control Input = [9.801 0.045]\n",
      "Current State = [62.355 61.534  1.051]\n",
      "Desired State = [62.322 62.684  1.056]\n",
      "State Error Magnitude = 1.1512068495097656\n",
      "Control Input = [4.914 0.023]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [62.599 61.96   1.054]\n",
      "Desired State = [62.884 63.681  1.059]\n",
      "State Error Magnitude = 1.7438104477444503\n",
      "Control Input = [8.181 0.028]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [63.003 62.671  1.057]\n",
      "Desired State = [63.442 64.679  1.062]\n",
      "State Error Magnitude = 2.0551114717885794\n",
      "Control Input = [9.82  0.025]\n",
      "Current State = [63.486 63.526  1.059]\n",
      "Desired State = [63.442 64.679  1.062]\n",
      "State Error Magnitude = 1.1535273162419732\n",
      "Control Input = [4.918 0.013]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [63.727 63.955  1.06 ]\n",
      "Desired State = [63.999 65.678  1.063]\n",
      "State Error Magnitude = 1.7444363823007047\n",
      "Control Input = [8.182 0.012]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [64.127 64.669  1.061]\n",
      "Desired State = [64.555 66.677  1.063]\n",
      "State Error Magnitude = 2.05277225568323\n",
      "Control Input = [9.808 0.005]\n",
      "Current State = [64.605 65.525  1.062]\n",
      "Desired State = [64.555 66.677  1.063]\n",
      "State Error Magnitude = 1.1522872593714653\n",
      "Control Input = [4.906 0.003]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [64.844 65.954  1.062]\n",
      "Desired State = [65.111 67.673  1.061]\n",
      "State Error Magnitude = 1.7395970175525388\n",
      "Control Input = [ 8.157 -0.005]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [65.241 66.666  1.062]\n",
      "Desired State = [65.667 68.665  1.059]\n",
      "State Error Magnitude = 2.0439536784119077\n",
      "Control Input = [ 9.766 -0.015]\n",
      "Current State = [65.717 67.519  1.06 ]\n",
      "Desired State = [65.667 68.665  1.059]\n",
      "State Error Magnitude = 1.147422509486637\n",
      "Control Input = [ 4.879 -0.007]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [65.956 67.945  1.06 ]\n",
      "Desired State = [66.224 69.653  1.055]\n",
      "State Error Magnitude = 1.729249122723198\n",
      "Control Input = [ 8.106 -0.022]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [66.352 68.652  1.057]\n",
      "Desired State = [66.783 70.634  1.05 ]\n",
      "State Error Magnitude = 2.0286572409941694\n",
      "Control Input = [ 9.692 -0.035]\n",
      "Current State = [66.828 69.496  1.054]\n",
      "Desired State = [66.783 70.634  1.05 ]\n",
      "State Error Magnitude = 1.1389245265857684\n",
      "Control Input = [ 4.836 -0.017]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [67.067 69.917  1.052]\n",
      "Desired State = [67.345 71.607  1.044]\n",
      "State Error Magnitude = 1.7134491405252712\n",
      "Control Input = [ 8.03  -0.039]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [67.465 70.614  1.048]\n",
      "Desired State = [67.909 72.571  1.037]\n",
      "State Error Magnitude = 2.007006473427949\n",
      "Control Input = [ 9.589 -0.056]\n",
      "Current State = [67.944 71.445  1.043]\n",
      "Desired State = [67.909 72.571  1.037]\n",
      "State Error Magnitude = 1.1268317005459427\n",
      "Control Input = [ 4.778 -0.028]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [68.184 71.858  1.04 ]\n",
      "Desired State = [68.478 73.524  1.028]\n",
      "State Error Magnitude = 1.6923532462402429\n",
      "Control Input = [ 7.929 -0.057]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [68.586 72.541  1.034]\n",
      "Desired State = [69.051 74.465  1.018]\n",
      "State Error Magnitude = 1.9792539576177628\n",
      "Control Input = [ 9.456 -0.079]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [69.069 73.354  1.026]\n",
      "Desired State = [69.63  75.392  1.007]\n",
      "State Error Magnitude = 2.1139569274989234\n",
      "Control Input = [10.169 -0.096]\n",
      "Current State = [69.596 74.224  1.017]\n",
      "Desired State = [69.63  75.392  1.007]\n",
      "State Error Magnitude = 1.1689070265958057\n",
      "Control Input = [ 5.056 -0.048]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [69.862 74.654  1.012]\n",
      "Desired State = [70.215 76.304  0.994]\n",
      "State Error Magnitude = 1.6877531465360078\n",
      "Control Input = [ 7.931 -0.089]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [70.283 75.326  1.003]\n",
      "Desired State = [70.806 77.2    0.98 ]\n",
      "State Error Magnitude = 1.9454610093924443\n",
      "Control Input = [ 9.305 -0.117]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [70.783 76.111  0.991]\n",
      "Desired State = [71.406 78.077  0.964]\n",
      "State Error Magnitude = 2.0628268038450575\n",
      "Control Input = [ 9.931 -0.139]\n",
      "Current State = [71.327 76.941  0.977]\n",
      "Desired State = [71.406 78.077  0.964]\n",
      "State Error Magnitude = 1.1384427274480786\n",
      "Control Input = [ 4.926 -0.069]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [71.603 77.35   0.97 ]\n",
      "Desired State = [72.013 78.935  0.946]\n",
      "State Error Magnitude = 1.6376838368200928\n",
      "Control Input = [ 7.699 -0.123]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [72.038 77.985  0.958]\n",
      "Desired State = [72.629 79.772  0.926]\n",
      "State Error Magnitude = 1.8828243987587208\n",
      "Control Input = [ 9.012 -0.159]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [72.556 78.722  0.942]\n",
      "Desired State = [73.255 80.587  0.905]\n",
      "State Error Magnitude = 1.991999705420855\n",
      "Control Input = [ 9.598 -0.187]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [73.12  79.499  0.924]\n",
      "Desired State = [73.891 81.378  0.882]\n",
      "State Error Magnitude = 2.0321867901077932\n",
      "Control Input = [ 9.823 -0.21 ]\n",
      "Current State = [73.713 80.282  0.903]\n",
      "Desired State = [73.891 81.378  0.882]\n",
      "State Error Magnitude = 1.1107607012579677\n",
      "Control Input = [ 4.856 -0.105]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [74.013 80.664  0.892]\n",
      "Desired State = [74.539 82.144  0.856]\n",
      "State Error Magnitude = 1.5717679432709994\n",
      "Control Input = [ 7.413 -0.179]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [74.479 81.241  0.874]\n",
      "Desired State = [75.198 82.884  0.829]\n",
      "State Error Magnitude = 1.7943782770083496\n",
      "Control Input = [ 8.61  -0.227]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [75.031 81.901  0.851]\n",
      "Desired State = [75.87  83.595  0.799]\n",
      "State Error Magnitude = 1.8911546960413503\n",
      "Control Input = [ 9.135 -0.262]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [75.633 82.588  0.825]\n",
      "Desired State = [76.555 84.277  0.767]\n",
      "State Error Magnitude = 1.9249238891922447\n",
      "Control Input = [ 9.33  -0.292]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [76.266 83.273  0.796]\n",
      "Desired State = [77.254 84.928  0.732]\n",
      "State Error Magnitude = 1.9277694316452907\n",
      "Control Input = [ 9.365 -0.318]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [76.921 83.943  0.764]\n",
      "Desired State = [77.967 85.546  0.695]\n",
      "State Error Magnitude = 1.9159123025781883\n",
      "Control Input = [ 9.324 -0.344]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [77.595 84.588  0.73 ]\n",
      "Desired State = [78.696 86.131  0.656]\n",
      "State Error Magnitude = 1.8976370745639357\n",
      "Control Input = [ 9.251 -0.369]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [78.284 85.205  0.693]\n",
      "Desired State = [79.442 86.68   0.614]\n",
      "State Error Magnitude = 1.877302339552811\n",
      "Control Input = [ 9.167 -0.393]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [78.989 85.79   0.654]\n",
      "Desired State = [80.203 87.193  0.57 ]\n",
      "State Error Magnitude = 1.8573402838981856\n",
      "Control Input = [ 9.085 -0.418]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [79.711 86.343  0.612]\n",
      "Desired State = [80.983 87.668  0.524]\n",
      "State Error Magnitude = 1.839246598433075\n",
      "Control Input = [ 9.013 -0.442]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [80.448 86.86   0.568]\n",
      "Desired State = [81.78  88.103  0.475]\n",
      "State Error Magnitude = 1.8240665793052333\n",
      "Control Input = [ 8.956 -0.464]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [81.203 87.342  0.521]\n",
      "Desired State = [82.597 88.497  0.424]\n",
      "State Error Magnitude = 1.8126296561161992\n",
      "Control Input = [ 8.918 -0.486]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [81.977 87.786  0.473]\n",
      "Desired State = [83.433 88.849  0.372]\n",
      "State Error Magnitude = 1.8056575501883765\n",
      "Control Input = [ 8.902 -0.505]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [82.769 88.191  0.422]\n",
      "Desired State = [84.29  89.157  0.318]\n",
      "State Error Magnitude = 1.8038083169837826\n",
      "Control Input = [ 8.911 -0.521]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [83.582 88.557  0.37 ]\n",
      "Desired State = [85.167 89.419  0.263]\n",
      "State Error Magnitude = 1.8076876262577568\n",
      "Control Input = [ 8.949 -0.535]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [84.417 88.88   0.317]\n",
      "Desired State = [86.067 89.635  0.208]\n",
      "State Error Magnitude = 1.817843650248185\n",
      "Control Input = [ 9.016 -0.545]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [85.273 89.161  0.262]\n",
      "Desired State = [86.989 89.802  0.152]\n",
      "State Error Magnitude = 1.8347547562522915\n",
      "Control Input = [ 9.115 -0.551]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [86.154 89.397  0.207]\n",
      "Desired State = [87.934 89.92   0.096]\n",
      "State Error Magnitude = 1.8588157259936489\n",
      "Control Input = [ 9.249 -0.553]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [87.059 89.587  0.152]\n",
      "Desired State = [88.903 89.987  0.042]\n",
      "State Error Magnitude = 1.8903263494918832\n",
      "Control Input = [ 9.418 -0.551]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [87.99  89.73   0.097]\n",
      "Desired State = [89.897 90.002 -0.012]\n",
      "State Error Magnitude = 1.929484919115574\n",
      "Control Input = [ 9.622 -0.545]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [88.948 89.823  0.042]\n",
      "Desired State = [90.91  89.975 -0.023]\n",
      "State Error Magnitude = 1.9692413293793378\n",
      "Control Input = [ 9.835 -0.324]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [89.93  89.864  0.01 ]\n",
      "Desired State = [91.902 89.992  0.076]\n",
      "State Error Magnitude = 1.976867792466491\n",
      "Control Input = [9.864 0.334]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [90.916 89.874  0.043]\n",
      "Desired State = [92.828 90.144  0.253]\n",
      "State Error Magnitude = 1.942171873873422\n",
      "Control Input = [9.608 1.05 ]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [91.876 89.915  0.148]\n",
      "Desired State = [93.682 90.448  0.428]\n",
      "State Error Magnitude = 1.9035144337618997\n",
      "Control Input = [9.324 1.4  ]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [92.799 90.053  0.288]\n",
      "Desired State = [94.47  90.889  0.589]\n",
      "State Error Magnitude = 1.893130155124486\n",
      "Control Input = [9.202 1.505]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [93.681 90.314  0.439]\n",
      "Desired State = [95.198 91.455  0.729]\n",
      "State Error Magnitude = 1.9202984935899001\n",
      "Control Input = [9.29  1.451]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [94.522 90.709  0.584]\n",
      "Desired State = [95.872 92.134  0.845]\n",
      "State Error Magnitude = 1.980208756886826\n",
      "Control Input = [9.559 1.306]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [95.319 91.236  0.714]\n",
      "Desired State = [96.497 92.913  0.939]\n",
      "State Error Magnitude = 2.061739037225767\n",
      "Control Input = [9.944 1.123]\n",
      "Current State = [96.071 91.887  0.827]\n",
      "Desired State = [96.497 92.913  0.939]\n",
      "State Error Magnitude = 1.1165650543910093\n",
      "Control Input = [5.218 0.561]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [96.424 92.271  0.883]\n",
      "Desired State = [97.081 93.779  1.013]\n",
      "State Error Magnitude = 1.6501234153202655\n",
      "Control Input = [7.911 0.652]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [96.926 92.882  0.948]\n",
      "Desired State = [97.629 94.72   1.071]\n",
      "State Error Magnitude = 1.9713882366670301\n",
      "Control Input = [9.513 0.615]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [97.481 93.655  1.01 ]\n",
      "Desired State = [98.147 95.723  1.115]\n",
      "State Error Magnitude = 2.175186300423606\n",
      "Control Input = [10.526  0.526]\n",
      "Current State = [98.041 94.546  1.062]\n",
      "Desired State = [98.147 95.723  1.115]\n",
      "State Error Magnitude = 1.1829875072312774\n",
      "Control Input = [5.397 0.263]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [98.304 95.018  1.088]\n",
      "Desired State = [98.641 96.776  1.147]\n",
      "State Error Magnitude = 1.7910545601286805\n",
      "Control Input = [8.569 0.291]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [98.702 95.777  1.118]\n",
      "Desired State = [99.117 97.865  1.168]\n",
      "State Error Magnitude = 2.129803337729748\n",
      "Control Input = [10.297  0.253]\n",
      "Current State = [99.153 96.703  1.143]\n",
      "Desired State = [99.117 97.865  1.168]\n",
      "State Error Magnitude = 1.1632224531639002\n",
      "Control Input = [5.215 0.127]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n",
      "Current State = [99.369 97.177  1.156]\n",
      "Desired State = [99.582 98.978  1.181]\n",
      "State Error Magnitude = 1.8139718223804633\n",
      "Control Input = [8.671 0.125]\n",
      "\n",
      "Goal Has Been Reached Successfully!\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "MovieWriter imagemagick unavailable; using Pillow instead.\n"
     ]
    },
    {
     "data": {
      "image/png": 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XYDV79mwGDRoEwKBBg5g1a1bF8dtvdys9evbsyeHDhytShiKSHHrhpqr24dbu9Ef1O9WdiJs6/B5uak9E5HjUOt310ksvmR07dphAIGC2bdtm7rzzTnPqqaeaxYsXm/Xr15vXXnvNtG3btuL6p556ymzcuNF8+OGHMdOA1W+1Tanppptuuummm26peRsDZmwSjCPet9riFst7kFBFRUX06NEj0cMQERGROHK8+8ep38rhZFVb3KLO6yIiIhJ3P4l43JyCqmNRYCUiIiJxNxl3EciXiR5IE1NgJSIiInEXrjU6KdEDaWIKrERERCSuyqgMrFoaBVYiIiISVxm4QdX3Ez2QBFBgJSIiInGzicrZqiXHuLY5Skv0AERERKT5eKcgn0+KS9g2biLs23/sJzQzmrESERGRuBgD7M3LZfWAvuxdVMgvnnuSU7JPT/SwmpQCKxEREYmLUwvyAbAzM0hLT+ecnhczYt5Ubhg5lNbt2yV4dE1DgZWIiIg02AW4s1XVpWVk0GvgAG579M9NPqZEUGAlIiIiDbYyyjFjDHYoxHuz5/PC0N83+ZgSQYGViIiINEgr3JWA1VmWheXz0a5zR47sP9DUw0oIrQoUERGRBvlXQT5LikuqHLNDIexQiBUz57L4mYkJGlnTU2AlIiIiDbIvL5eD3XIqPjaOw7Jps3jtmedbzExVmFKBIiIiUm/l3r2dmVFxzLZt94EVLUHYvCmwEhERkXpLj3IsLT29Ra0EjKRUoIiIiNRLvmqralBgJSIiIsctG9VWRaNUoIiIiBy3Uu++Sm1VKOQ+aIG1VWGasRIREZHj8ruCfF6vlgKEyi7r2Wd35ek77knAyBJPgZWIiIgcl7Z5uayOSAEChIJBHNtusbVVYQqsREREpM5mAJupmgI0xrD3061MGfZHdm7YlLCxJQPVWImIiEid9Y9yzLIsOnTvyoARQ5p6OElHM1YiIiJSJ5PUXuGYFFiJiIjIMZ0N7M/L5VBEbZVjOyydNpPFz0xsse0VqlMqUERERI7pY+8+XFtljMEOBbGwWnR7heoUWImIiEitdgHVQyfLskjPzGyxW9fEolSgiIiIxPRgQT4lxSX0mDC5yvFQeQDHOKqtqkaBlYiIiMTU2utZVXJTP8BNAYbKAyyfOUe1VVEoFSgiIiJRlXv3dmYGJi0NYwzGcXh/4WssHjdJQVUUCqxERESkiiEF+cwYOZTy9u2qHLcsC5/fz8XXX6u6qhiUChQREZEqOuXlsrVbDs8PuK7KcdVVHZsCKxEREQHcmaqjXgPQ6lvWOLbNqgWLmD9mrFKAtVBgJSIiIoA7U+XvloNd7bhlWVg+H+06d1RQdQwKrERERIRe3n3kTBWAY9vYwVDFKkCpnYrXRUREWrAhBfncN3Ior1YrVA+zfD5K131M4UOPa7aqDjRjJSIi0oKF038Tbri+ynHHtgkFgypUP06asRIREWlknYHXgdXAR8B93vF/AGuBYmAGcErEc4YDG4B1wPcbaVyfefd2ZgZORjoQ3gMwxHtzFvBw7xs1U3WcFFiJiIg0shDwf8C5wKXAPUAe8BrwdeB8YD3wgHd9HnCLd31v4Gni9wt7SEE+N48cymft27G/V48a51Wo3jBKBYqIiDSyXd4N4CjuLFUn3MAqbBlwk/e4H/AyEAA+BTYCl3jXHI8hBfl8WlzCa+MmcmTffsBN/Z3ZPYfnftgf4/dXuV59qhpOgZWIiEgT6gJcCCyvdvxO4BXvcSeqBlHbvWPHq1NeLh265XBJ/z6cM3Me33ztDaYDToa78s8Yg2VZNVb+aaaq/hRYiYiINJGTgOnA/cCRiOMjcNOFU47jtaLNRkU7lua1T/h04AA+veXGKq9hWZZ7H7HyTxpGNVYiIiJNYOhLE/hvtxymnXQihd6xIQX5PHldb/qlpfGTiGNtvnM5Z594YsVzv3X+1zln0I9pHdESoVNeLj0H9GXkgmncMHIordu3o1NeLpff0Je/vDqDKS8+W3UAvpq/8kPlAQJlZbzzynQm3f9AjfNy/DRjJSIi0giqzx7d8e+plPW8mOwh97Bo5jwuHTeR1/bv54rVa5k+fxrTl7/HN6bO5JW8XJx7fsY9pTu44J7B5M1dSIe16+nwy7v5869+Qaf33qfLu8v5L5WzUZf9sD+XDRwAVKb5dp1/XpXx2KEQTsgmPSuTUCCA41TWUin1Fz8WYBI9iKKiInr0qLkyQUREJBVEBlH/2LefQcDYkqX4ywNgHC59egI9J77I3nO6Y3w+MIZ37vs5331kDP5AkC/buI0Wdn7jXJb8YRgAlzw7ia8XzsVJ8/Pmb+/n08t71TKC2IwxGGN4t2AGi5+ZyOCxo9lc/KECqgaoLW5RYCUiInKcwoHUxnETeW3ffl6MCKK+snAxZy17j4V/f7DJxmOHQhjHIS2jcjuaUHkAX3oauzZ9wkvDHmTnhk1NNp7mrra4RalAERGR4/AOsCwvl7O65fDt/n1YtWAxULnH3pr+17Gm/3W1vkasQMgxDhlZWXU+Vj2l9+Cb82q0TNCsVNNS8bqIiEgthhTkM9trqOlQdbNiOyuLNQNqD6LADYbA3SYmWFbO0mkz+ev3B1ScC5SVsaxwNg/3vrHOx0rXrmfZjNlVuqOXrl1fcV4d0xNDM1YiIiIRwmm+EeMmcuG+/YzJy+WTbjl8ckNf2n7yKWUnt671+bFmlLp/80I2rXy/yixS6dr1Neqd6nps1MBBNT53tGPStFRjJSIi4rkKuDaiXip34WLWHiOtFwoESMvIqNFkU0XizZdqrERERGIYUpDPBcUl9B83kVb79jOaynqptf36xHye4ziEAoGYs1GaPWqZFFiJiEiLtQWYlpfLgW45PN//Ojp+8GHVC7zO5GHhNF/gyy9Z8593mD9mrGajpAoFViIi0qIMKcjnquISLh83kdbeti/hGaptl1ZN78RK8ymYklgUWImISIsRnqHa0C2HDf2v4/TVa6NeF26quWzG7KhpPpFYFFiJiEizVr2GCipnqHZ+84Iq16qppjSUAisREWm2bsLdrNitoerDWe+uiHpdxQxV4WzNTEmDKLASEZFmKQj4ocoqv81XfrvKNZqhknhTYCUiIs3K2IJ8zi4uoWzcRLIOHYp6jWaopLEosBIRkWahFXAYGJOXy+puOay+oS+ff/ElWRHXhAIBfGmaoZLGo8BKRERS2pCCfC4uLuG6cRPxVStOz/I2OXYcBzsQVLsEaXQKrEREJKV1ystlj1ec3u3N/0a9xrIsStd9TOFDjzfx6KSl8SV6ACIiIvXxB8DxHtuZGdhZWaz/wVVVrgmVBwiUlfHOK9OZdP8DTT5GaXk0YyUiIilnYkE+nYtLODpuYpXjlrcFjYrTJVEUWImISEqxcQvUD3fL4aMb+lY5FwqG8Pl9Kk6XhFFgJSIiKeEmoAAIb4scLlAHb4bKcVg1b6E2RpaEUmAlIiJJL9yb6ui4iWQe/qzGecuyMJZFu84dFVRJQimwEhGRpHYImBDuTTXgOg4eOcrJEedD5QEc47Bi5lwWPzMxxquINA0FViIikrRCVC5fD6f+Ts7MBMCxbexgSL2pJKmo3YKIiCSlyQX5vDFyKEfbt4t63vL5KnpTKaiSZKEZKxERSSrZwA5gdF4uB7rl8MGN11eZBQgFAjiOUn+SnBRYiYhI0ugDzKHqyr9wUGWMwbFtVs1fpJV/krQUWImISFJ4pCCfi4pL+HzcRE7w9vyLZFkWls+nlX+S1BRYiYhIwj0K+MIr//pfx47SHXSIOK+Vf5IqFFiJiEhCjQfuAkZTufKvQ/euADiOgx0IauWfpAwFViIikjD/LMgnJ8qef2GWZVWs/BNJBQqsREQkIaYCWyPSf5FCwSCObSv1JylHgZWIiDS58cCNVE3/QeSef69q5Z+kJDUIFRGRJvUwbk1VNJZlgfb8kxSmGSsREWkyQ4DOBfksKS7homp1VUr/SXOgwEpERJrEVcBjuB3V93fL4f2b+uHHTf/ZwSDLZszWyj9JeQqsRESk0WUDr1HZUd3JzKgIqozjsGr+IhaPm6SgSlKeaqxERKTR/aMgnyUjh3Kk2obKlmXh8/u5+Pprue3RPydodCLxoxkrERFpVDYwxttQedUNfav84lFHdWluFFiJiEijsalMjdiZGRW/dCo2VF6gDZWleVEqUEREGsWkgnxej5L+A22oLM2XZqxERCTutgDT8nI51C2H4v7XVRStA4QCARxH6T9pnhRYiYhIXE0CzvQe25kZFUFV5ApApf+kuVJgJSIicdML8HkNQKuzLAujrurSzCmwEhGRuHmHygagkdRVXVqKBgVW999/Pz/72c8wxlBSUsIdd9zBGWecwcsvv0y7du1YuXIlt912G8FgMF7jFRGRJDU5YqbKqbax8t5PtzJl2B/ZuWFTooYn0iTqvSqwY8eO3HfffVx88cWcd955+P1+brnlFh555BFGjx7NOeecw8GDB7nrrlhbbYqISHPxBbA3L5fVA/rWOGdZFh26d2XAiCFNPzCRJtagdgtpaWmccMIJ+P1+TjzxRHbu3MmVV17JtGnTAMjPz6d///7xGKeIiCSRzsDrwGrgKJDlHU8v+5IbB9/HHX1+yI2D7yP94EGCZeW8+8p0zvvfIWwAioELEzRukcZW78Bqx44dPPbYY2zdupWdO3dy+PBhVq5cyaFDh7BtG4Dt27fTqVOnuA1WRESSQwj4P+C3wInesVM3babHhBfY2vNiJs6bytaeF9Nz4hRK131M2cOj6FJWzjnA3cDYRA1cpJHVO7Bq06YN/fr1o2vXrnTs2JGTTjqJ3r171/n5gwcPpqioiKKiItq3b1/fYYiISALsAt4Hbvb2AAxlpNNq9166v/E2a/pdi2PbfND7KjrNms+k+x+gHzDZe+5yoA3uxswizU29A6urr76azZs3s2/fPkKhEDNmzOCyyy6jTZs2+P1+ADp37kxpaWnU548fP54ePXrQo0cP9u3bV99hiIhIgti4dVVbe17Ml23bsusb53Li/gMcbnMK704tZORPBnPSgYMc2X+ATsC2iOduB5TPkOao3oHV1q1bufTSSznhhBMAuOqqq1izZg1vvPEGN910EwCDBg1i1qxZ8RmpiIgkjU2ABaR/8QV9hv2RN4f/mkCrkwBYNe9VFo+bxJEDBzEJHaVI06t3YLVixQqmTZvGqlWrKCkpwefz8eyzzzJs2DCGDBnChg0baNeuHRMmTIjneEVEJMFuArp6j/v+egRr+/yAjVd/B4Av2p3KFb0u4bZH/0w2sMe7rpTKbuzgFr9Hz2eIpDYLEv8HRVFRET169Ej0MEREpA4mF+RzxgcfcvnjT7L6h/15c9ivAQgFglwx+l+sLy3lng/X8P/2H+BUYBhwLXCvd98T+Kd3L5KKaotb1HldRETqLAQ8kZdL1mefkVke4MzlK7n1ptsxxjD+wvO4edEbTDh4iJW4GzEP9J43Hzeo2ojb8+qOxAxfpNEpsBIRkTopobJ+ZFvPixlVshQAx3F4b/Z85j/xDEcOHuLqGM+/tykGKZJgCqxEROSYrgLeL8hnV5TNlX0+Hxdffy3tOnfk6TvuafrBiSQRBVYiInJMrxFjc+VAEMfR5soiYQqsRESkVgHclU4QZXPlLdpcWSRSg/YKFBGR5m0K7l/g0ZaPa3NlkZo0YyUiIjHZBfksKS7hrHFV03yhQADHcZQCFKlGgZWIiERlA2O8uqpVN/St+IURCgRYNmM2i5+ZyJH9BxI5RJGko8AqiQwpyOfT4hK6ffMCPln5Aa+Nm8iRffsTPSwRaYHeAaYU5ANuXVX4l4XjOKyav8jdskZBlUgNCqySSKe8XM44pzu+ND/ZZ3fj0pv6s2ruQuY9MVYBlog0mVZAL2BZXm6Nc2qtIFI7Fa8nGV+aH3CLQv1pfi7udy1/WDybW/7yO1q3b5fg0YlIS3CYylWAkYwx2KEQ782ezwtDf9/UwxJJCQqskpxlWfj8Pi7udy1DpuYruBKRRrWZ2JvIWpaF5fPRrnNHpQFFYlBglSIsy6J1u1MVXIlIo7kAeLsgnyUjh1JQ7edMKBAgUFbGuwUzNFslUgvVWCWJIV6RaG3CwdWvX5nI6JvvUN2ViMTVSipXAQa8VYDGGEKBAMsL52gVoEgdaMYqSXSKUiQajWVZtG7fjtse/XMjj0hEWpJtVO2unpbhdlg3xvD+gte0ClCkjhRYJSsTrcLB/SG3e9NmCh8e1cQDEpHmKhvoFONceBWg/pgTqRsFVsnKsqIGV9pCQkTirRR4sSCfxSOHVjkeCgZVVyVynFRjlWKMMRjHYf/2HbRu3051ViLSICW4KcC9ebns7J5T8UvBDoVYNn2W6qpEjpMCqyQQWbh+0eR/8/UZcwA4ckYHZo/5Oyft3U+f3/6eEw4dZvfXvsqCv/1RDfpEJC7OjXgcWVflhGwsLHf2XETqTKnAJBAuXG+1ew8XvjSVl15+nskzXyJw4ol8beY8Lh/9L1bddgvPz59G2cmt+fr02aqzEpEGm+y1VjharbWCZVmkZ2XSa+AA1VaJHCcFVknGF7Lxl5XjlJXR9tOtfOuJsZy1YiXrv/ddANZcfy1nv/G26qxEpEGW4Kb/Vg/oy9MLplc5FypXzyqR+lIqMIkc7XA67/30xwz+/gBCWZns/crZnLZ+I4fP7IRJc79VR7JPp9XuPaqzEpEGKfVKEOzMDNK9Y8YYHNth1YJFzB8zVrVVIvWgGaskknn4M7q/8Tbj5rzMoJ//lI4ri6Pu14Vl4U9L0xJoEamXEO5sVXXuljWWtqwRaQDNWCWRs5YV8VmnM/iybRscfxqfZGbylWCQrEOHsUIhTFoarXft4ejppxEKBFg2YzaLn5mY6GGLSAp5mOh/UbuzVTYr5y5k/pixTT0skWZDM1ZJ5MgZ2WR/uJos26HXD/tz8BvnYoDMI0fJfe0NAL42ez6bvns5WJZW7IjIcRse47g2WBaJD81YJZFd3ziXDVd/l5/88HY+/+IL3j18hJ7euW9O/jeXPTmOPV/N5aMb+pKWnk6vgQPIPrurWi6ISJ08X5DPkuISeo6rOtNth0LYoRArZs7VLLhIAymwSjLv3vMz3hp8OysK5/LauInc7BWmv/Tv56tcZ4zhvdnzNWUvInVyNnAwL5fPuuVQ3L9P5b6AjsPSaTPVCFQkTpQKTDKWZZGeWdk/xkD0Anbgwt5X871f3Enraj1oRESq+9i7tzMzsLKy3F0cjGH1G29rg2WROFJglWSM41TpHxNupNB+7foq17kN/LLUwE9EjmkJNf9AsywLy7I497uX62eISBwpFZgsjAHLIvBlGU/edjc7N2wC4P8BBcBtAwcxumRpladoZaCI1EWpV1sVyRhDsLxcdVUicabAKll4q/vSszL51UvPsWLmPF4bN5FptTX/1MpAETmGcuCpvFz2d8sB3IDKsizW/Xcpr/z+IaUAReJMqcAk4/P7j5niy/zsCNcNGcHPbriVZ1+ayh9+/lPaAouA9d59m6YbsogkqZ9ARVd1J9PdYNmyLBzb5kDpTv1RJtIIFFglGce2j7lH13ceGc2nl13K8zNf4n9vHsATT09gOG4dRa53H6tXjYi0HC8QffGLz+9XfaZII1EqMFl4NVZfHjnK2DvvqaixAjBURsAZR47S+b0PePWvv6fsyBEWPvcCRw4eoh/wHe+afOBNFFyJtGTvAC8W5HNGtdoq9awSaVwKrJKFNyV/QutWVWqsjuzbTxlwIu7KQMuCL09tww9+91dOW7+Bvpf15JHcs+nw2JPsMgaAXUCHhH0hIpIMegHL8nLZ59VWgbvqePn02SwaO0G1VSKNRKnAJBOtxuo/3rlbBw7CZ9ucvnY9xTffwItTJ2O3asUvDx0mIyuryuuYJh63iCSPz3FnqwCMV1sF7myV8WbHRaRxKLBKsCHeD78wOxSqUWN1LVQ0Cj3S4XSOdDiNXd84F4CPr7qCzP/8l9LycrK918gG9jTVFyAiSSUbOAHYm5db41xaRoZqq0QamVKBCdYp/MPP+ytyx8cbmXDP/8Wcpv+ifTuOZHeg7eYtHOzahbOWv0fwkotZc2pb7v5wDX/+4gsGAbOa7ksQkSRSSvSCdWMMjm2zcu5CbYUl0og0Y5UsvKn5jrln17pNTena9bzxwBCuGf4gt91wKx3Wb+K9X9zJtkf+zI+7dGY9cDXw96YbuYgkiUdxg6popQCWZWH5fLTr3FH1VSKNSDNWScafnkavgQPIPrsrT99xT43zzw4cxJ9KlvLSK+5qHse2CQWDrJg5lxF79nGkqQcsIkmjg9dhvdu4qqv9QoEAjuNoJaBIE1BglWTsYJCl02fV+OEXbrlQAKylsntysDzAk7cOrtKeQURans3AjLxcDnTLYeWA6yoag4YCwYqtrzRTJdL4lApMBsa4N+CtKa9Q+NDjNX4Ahrz7y7x7y0sdZpyQxa9eeo4bRg6NmT4Ukeavi3dvZ2aQnpkJuH+ArZr/KovHTVJQJdJENGOVDCKWPn/7J7eQkXVCRQ+rsF3AWcBJNZ5qVbRniJU+FJHmLT/KJsvg/ny4+Pprade5o342iDQRBVZJJlaN1T+Ap4i+2idYVs7ymXNUOyHSAl0F7MvL5WBEI1CoWn+pnw0iTUeBVZKJVWP1L+BJKgMr46UOLcui4E9/Z9XchU06ThFJDoMK8tmLmwIMM8awd8s2Xhj6O9VfijQx1Vglg5ANIbeK6rXxk6LWWFVnWVZFndXNfx6hGiuRFmg20RuBWpbFaTlnMWDEkKYflEgLp8AqGVhgRU3y1U1aerq6KYu0QNdFOWaMwQ6FeG/2/IrdG0Sk6SgVmAz8/oqGft8bfAetTz21RvF6bYzj8N7s+eqmLNKC7Cd6zaUagYoklgKrJFNbg9BwL6vqjIELe19NsKz8uAIyEUlNrYC21Oyw7tgOoWBABesiCaTAKsnEKl6Hyh+ip6xdz+GIugqf34fPr5YLIi3FYeDFgnyyvRYL4cUs7y9YxJzHntRMlUgCKbBKNpbl1ltZNSf5y4ETgZ8MHMTTJUsrjhtjCJUH1HJBpAW4BzcFuDcvl53dcvB7uzCsKJzLK394KNHDE2nxVLyeZPxpaTEL0Td69xk1zrhiBWQi0nxEtl1Jy8zAsiyMMVx4zfe0OlgkCWjGKsnYwRBLp8+MOvP0F2BqlOe43dczlQoUaeZW4qYAz6jWZV0/A0SShwKrZGEMWBa7Nn0Sc1+vabh1VlG7r5eXs7xQqUCR5uxC4M28XPZW67IeKg/gGEdF6yJJQIFVgpWuXU+nvNyKFF722d0ZuWAaK2bOO+YKv8ju6zMf+SfLps5okjGLSNOrsh9g9S7rW7cxZdgf1WVdJAmoxirBRg0cVOVjf5q/YlPlYzX8jOy+PuCB+1VfIdJMnY27H+DqAX1rnLMsiw7du6rLukiSUGCVZBzbJlBWxrsFM46ra7K6r4s0Xx9795H7AYL78yJYVn7cPy9EpPEoFZgsHAd8PnZ/8injBt933H1o7FCIpdOiF72LSOoaS/S6SgDL56N03ccUPvR4Uw5JRGqhwCrJ+Hy+WlsmVO++brweNod27YlZ9C4iqeukyNoqjzGGYHm5itVFkpBSgcnC534rTss5i5ELpsWsl4rsvg5U1Fi17Zhd6/NEJPWU4jYCDddWhResfPzOch7ufSOFDz2uP6ZEkowCqyTj89devB7w7n9crejd5/PVuehdRFLDGd59uLbKsiwcx2H/9lI1AxZJUgqskowxBmMMuzZtpvDhUTXO7/Xuq3dfN8bUq+hdRJJTkOi1VT6fT39AiSQx1VglmXBqL9tbPl29g/IbwCAqf+BG9rJ68rafs2Pd+qYbrIg0ipuAf0fpsO7YNqFgULVVIklMgVWScRyHUCAQ8wfnvcDtVAZWVkQ64L4Xn2VF4dxjNhYVkeT2CjAmL5f9ER3WjTEUzZ7PgieeUV2VSBJTYJUsbBv8fo7uP8CoHw6K+YPzaC0vkZ6pvcJEUt0SYEpBPgBORN8qJ2QTKg+otkokyanGKslYfn+9f3CGAgHVWImkuO/irgSszp+eptoqkRSgwCpZ+P0AtGpzSgPaJlhYWPqLViRFfUb0gnVjDHYoxHuz5+sPJ5Ekp8AqyVgNaJuQlqFtbURSVSvvZqKcsywLy+ejXeeOqq8SSXKqsUoyDemobAdDLJ2ubW1EUtHTXof1nuOqvn9DgSCOY2sloEiKUGCVLLzidTsY5OHeN9b6V2msbW32fLpF29qIpKA/4NZVHeiWw8r+fUj3jtuhEMtmzGLxMxP1vhZJEUoFJhnfcRSvp1Xb1qZDtxxtayOSgh707u3MDNKzsgD3D6YPFi7WH0siKUaBVbLwitd9fj8jF0yvNTgK12BcW31bm2NshyMiyWdtjOOWZXHhtd/Xe1kkxSgVmITSs2rvRxUC/ECHaseN4xCspbmoiCSfooJ8tlfrsK73skjqUmCVhIJl5SyfOSfmD9SjQCaQ5X0crrGyQyH++eOfsXPDpqYaqog0QDnwVESH9fB7ueT1t5jx10eVAhRJQUoFJiHLV3s/qk+8e3/4eu86f3o6v3rpOdVYiaSAXsAr1TqsW5aFY9vullTqRyeSkhRYJaG0jIxa66QKYzzPsizVWImkiP8SvcO6z+/Xe1gkhSkVmISC5QGWF86OmQr8G/AQ0Ts0B8vLWV4YO40oIok3hdgd1h3bZuXchcwfM7aphyUicaDAKlkYb62fZTHj4cdYMWNOvV9K29qIJLcfxTiuDusiqU+BVbKICIRuHPkbOud9hdfGTXRrLY5DembtKwpFJLH2AC8W5HNGtZWAdiiEHQppJaBIilNglYTCe/7VJzgKBQIsmxE7jSgiidUet7ZqT7ecinSg4zgsnTZTHdZFmgEFVkkoFAyybPqsOgdHjm0DFj6/j6kP/p335ixo3AGKSL2EqKytsryVgMYY7GBIKXyRZkKBVZLwlQcwfh8mLY3Xx0/m1bHP1f3JBrDcGq3MVic1zgBFpEHuwV2GbaodtyyL9MwMpfBFmgkFVkmgdO16umWfRuvde9n31VxMjR+9tfOl+Sse9/vNfXTollOv+iwRaTxP4tZWtatWWxUKBHAcR7VVIs2EAqskMGrgIB4vWUqgdWsAvn7lt1k6dWa9AiN/ev3rs0Skcaz27vfm5bKze07FD147GKyoiVRtlUjzoMAqiZg099txxjndGblgGitmzos582SI3t3VDoUqimBFJDmsLMhnhzdTlZZRWVvl2I5qq0SaGXVeT0I+v/+4O6gbrw/W/u2lLB43SX/9iiSJAO5M1UcD+lY57u6UkKku6yLNjAKrJGQcQ6CsjHcLZvDC0N/Xem3rteuByv0C25/ZmZELpmm/QJEk0IfKtEB4P8Awx7YJlpXX6X0uIqlDgVUysrwOzLWkCGzv/oaBg6ocr89sl4g0jtlE37oGwPL5KF33MYUPPa4ZZpFmRDVWSchdfl17B/UgkA6cWO24MYZQeYDlM7VfoEiiTABuBT47sxPv3e5uYHPauvVc/Zd/4C8vx/b5GN3zYibNWQjAE8C1wBfAT4H3EzJqEYkHBVZJyBhDsLy81uXXh3GDqvTor6CCWJEEmgTcAYQyMynxaqsuH/Uv3v35Hfx75x544mnuXfsSjwLXAOd4t57AWODSxAxbROKgQanAU045halTp7J27VrWrFnDpZdeStu2bVm0aBHr169n0aJFtGnTJk5DbQFsN8EXKg/wcO8ba00RbPXuq38D3YJYpQJFEulVKlOAJlxbZVmkf3YEYxxOBnZ45/sBk73Hy4E2QHaTjVRE4q1BgdUTTzzBwoULycvL4/zzz2ft2rUMHz6cJUuWkJuby5IlSxg+fHi8xtpi+NPTjznbFCtVYEzdC99FJP4uAKYV5PPfewZXOf7msPv5zhPPMPG5yYzy+3nAO94J2BZx3XbvmIikpnoHVieffDLf/va3mTBhAgDBYJDDhw/Tr18/8vPzAcjPz6d///5xGWiL4Hc7qPv8PkYumF7ryr5p1T52vNkux7aPOdslIo1nJW57hfU/uKrK8fNemsaSX/8vP/3ZbfwqFGJCYoYnIo2s3jVWXbt2Ze/evUycOJHzzz+flStX8qtf/YoOHTqwa9cuAHbt2kWHDh3iNtiWJNzfJlbx+hK8LQLDB7xdcPxpaVh+f43rRaTxTQWmFLh/WDoZle0VjDF8bc58+q58n50bPwHcLW4ASoEzI16js3dMRFJTvWes0tLSuOiiixg7diwXXXQRn3/+edS0X7hxZXWDBw+mqKiIoqIi2rdvX99hNFvB8uPrbxO5X+CIeVPVx0okAW7Ena2qzrIsvuhwOr+90S1kvxLY4J2bDdzuPe6JuzBlV6OPVEQaS71nrLZv38727dtZsWIFANOmTWP48OHs3r2b7Oxsdu3aRXZ2Nnv27In6/PHjxzN+/HgAioqK6juMZsVXHsBJTwOfj/whI1j71rv1ep1jzXaJSPwdpnIG+drf/oHORas44dAhBl91Pe/84k7+edUV9H/sKT4AyoC7vWvn47Za2IjbbuGOph64iMRVvQOr3bt3s23bNnJzc1m/fj1XXXUVa9asYc2aNQwaNIhHHnmEQYMGMWvWrHiOt9kKlJWRva2UzKNH2Xnh+RjHqfdrBcvLWV6oPlYiTeUCoDUVGXnm/6PqilzHcdi36gMuem4y0dzbmIMTkSbVoD5Wv/zlL5kyZQoZGRl88skn3HHHHfh8PgoKCrjrrrvYsmULAwcOjNdYm7WMrCwOnXUmxkvptT3j+BZch1OulmXx4rAH+WjJm/EeoojEsBJ3tipU7XgoEMBxnFp70olI89KgwKq4uJgePXrUOH711Vc35GVbrMi9xAY8MIQzcs/mtXETObJv/zGfa0W0Z7jtH39i+Yw5dX6uiNTfm7gF62cUlzBw4ov8zjtuB0MsmzGbxc9M1ApdkRZEndeTlD89vd51UmkZGaqxEmki3wZG5+Wyr1sOD9zUD4AvPjvCYzfcyuHd0WtMRaT50ibMScpxHIpmz69Xk09jDLs3babw4VGNMDIRCQtQtcO6P839WzUjK5Orfna7VuaKtEAKrJKVMVzU+2q+94s7j/uHs2VZdOjelQEjhjTS4ETkLuDlgnwWjxxa41x41ljbSom0PEoFJonStevpFNH/xuf34/P765XSCwWDLJs+S8WyIo1oPG4KcH+3nCrHVbAu0rIpsEoSowYO4vGSpRUfO45DKBCo8w/ncHsGy+fj1aef4/UYy7pFpOG2AC+GO6xnVu2wvnfLNqYM+yM7N2xK0OhEJJGUCkw23p5/Xxz+rE57/lm4s12Wz4fjuC0Xzv3Ot1TbIdJIWuFuQROrw7rS8CItmwKrJJWekQERLRSiCTcjLB44CAC/1wPrzHPzGLlgmra1EWkEkR3WIxljsEMh3qvnohMRaR4UWCUbbwPljBNPqHNwdFn1l0hLIz0rS8WzInG2CDeoirYDqmVZWD4f7Tp3VN8qkRZMNVZJyrKsiuDoWMXr5wFbIz42jkMoEGT5TG1rIxJPuwryWVJcQttxVd9XKlgXkTAFVknMGMOuOvSj6kjVwMp7NhbWMdOJIlI3QeCf3irA8gF9Scd9j4YCQZYXqsO6iLiUCkxilmWRXUshbDgd0b7683w+pQJF4mgM4PceO5kZpHsrAY0xvL9gEYvHTVJQJSKAZqySWigQqNhrLJpwYNW62nHHtgkFg0pLiMTJfTGO+3w+Lr7+Wtp17qjto0QEUGCVfEK2Wx3r9zPjb6NYPm1WzEsd7/7E8MeOg8/n40DpTp66/ef6C1okDr7E7Vl1RnFJleOhYAjHDukPGBGpQoFVsrEqVx2deHL1uaiqbO8+PXzAm8Ky/D7VVonEwV1AJm7Pql3dcirTgbbNsukzVVclIjWoxirZ+P0Yr+XCNb/8ea3tFoLhp3j3Pr/77Wx7Rrb6WInEwRUF+Szx9gL0R9RV2aGQFoeISFQKrJKYPy2t1gL0Mu+++jfRp+J1kQY7jDtTtXpA3yrHLcsiPTNT7y8RiUqpwCTm2DbvTi2MWb9xFDidmoGVcRyCx7HPoIhUdReVi0LsiL0AwX1f2sGQ+sSJSFQKrJJMqDxAhgVORgYbi1ZR+NDjMa895N2HkxGObePz+zl66DCP33Craj9E6mk80betAbedSem6j2t9b4pIy6XAKomUrl3PKdmncXbJGj799mVknnhirdcfiXHc51Pxukh9fUH0VYCO7RAKaiZYRGqnwCqJjBo4iMdLlrL10ksAOL1rF1q3b8eRffujXv9ZtY99XtH7iaeczMgF01gxcx6vjZsY8/kiUtUfgCzc2qrd3XIq0uyRaXnNBItIbVS8noScDLeBQlark2pd3bc7xvMj9xlUca1I3T0Y8dinVYAiUg8KrJLYsQKkvTGeZ4zBGMPuOuwzKCKufK+1wtFqf8RoFaCIHA+lApNcsLyc5YXRVx+VxniO5f1V3cHbZ1BbbYjUbjywLy+Xg91yeL//dRW94cBdUOIYR7VVIlInCqySnGVZMVMQ62I8xxhDsLxcvwhE6iizIB9wWyuEgypjDI7tsGrBIuaPGavaKhGpEwVWSS4tI4NeAweQfXbXGjNPq6tdG263ECoP8HDvG/WLQKQObGBMXm6N45ZlYfks2nXuqPeSiNSZAqskFwoGWTZ9VtSZp13efY25LAsV2YrUwWqi96tyZ6tsVs5dyPwxY5t6WCKSwlS8nowcx70Bb06cQuFDj8f8i9lEPA63W0jLyNBegSLH0AvIi3HOna3yabZKRI6bAqskU7p2Pfh8WF5g9bUrLjvu4EjtFkSO7X+9VYCHq72/QoEggbIy3i2YwQtDf5+g0YlIqlIqMMmEm4SaNPdbk312t+Nu9mmMO4+ldgsi0ZUDT+XlcqBbDisH9CXdOx4KBFk2Y5YagYpIvWnGKsn5/P7jnn2yLAvLsiraLYhIpdlQEUjZmRmke41AHcdh1fxXWTxukoIqEak3zVglufq0TlC7BZHoWgHXxTjn8/m4+Pprade5o3q/iUi9KbBKAbX1sooUbrdgWZbaLYhE8XRBPkuKS+g5ruofHKFAEMex9ceIiDSYAqskF7mdRrReVlUYd7bKsix8afrWikQ6BEyIVlcVVF2ViMSPaqxSQLCsvE4rlHxp/ortbB6YW6B2CyKeScDJ3uPIuirjOKyap7oqEYkfTWskq5ANPgt8Pib88jdsWFZ0XE9Pz6rjLJdIM3c24PNSgNVZqqsSkThTYJWsIsqpWrVre9xPN8ao3YIIsB4YnZfL/m45VY6HgkEcW3VVIhJfCqySld9f8fCWv/yOrhd8o859rIAq7Rb0l7i0VPkRM1WOl/4D9w+PvZ9uZcqwP7Jzw6ZEDU9EmiHVWKWAtPT04+6irs7R0tJtAfbl5bJ6QN8a59TnTUQai2asUoDjOBTNns+CY2wG69g2ls+HZVn8/bqBHN69t4lGKJJc/gCc6T22I2aqwH2f2MEQy2fOUQpQROJOgVWKuKj31YTKymtPB0buyEztPa9EmqtWwIO1nLd8PkrXfUzhQ4830YhEpCVRKjAJla5dX+Vjn89Xp21t1G5BxGsCOnIoR6v9v+/YNoGyMt55ZTqT7n8gQaMTkeZOM1ZJKLwRc1h9tqhRuwVpiQLAk14T0FU39K34AafNlUWkqSiwSmamMreXc3U/7jz8GXuA87xjkU0Ybhx8H3Mf+yvlp5wMxvCdv4/irNffYs+BQywF3m/CYYskwg4qf6DZmRkVj7W5sog0JaUCk5nl7g9oWRb2o3/hH3fehi+iDcPwiEu39ryYSya8AEDXt5fSdst2Ji2cwbzf3kftJe8iqe+pgnxWR0n/QeXmysezqlZEpL4UWKWI3b0uIfemfrTJPr3iWL+I82v6XUv3N94CoPsbb/HhNVfz7tRC/jL2edoA2U06WpGmcxNQ7rVVeH7B9CrnQoGAWo+ISJNSKjBFhAIBVs5byLd27ak41iHi/Oft23HiPjfN0WrPXv71jyd47bMjAGwHOgG7mm64Ik2iFVAAjKZqWwVjjLsP4PxFzB8zVilAEWkymrFKEZbPh1VbCwXLqtphwVK7BWnehhTkUzhyKJ9HSf9ZXhq9XeeOCqpEpElpxipF+NPSuKjPD2gzcy6U7gRgN3CKd/6kvfv4ot2pABw9/TTu/c19tP6yjNfGTaTzvv2UJmbYIo2mU14uq7vlsLp/nyrHQ8EQjh3SHoAikhAKrFKEY9s1UoGzgaHe46/Nms+m714OwKbvXs4FL02j178e41ILDv/1MaUBpVmZXJDPXqJ0VXccVs1bqPSfiCSMAqskZhwHyxjw+/nuL+7nJ8veoz2wDfgj8HcqA6uzlhUx7/G/AvDJt3rR9a13ueMHN7Dn4CFuS8zwRRrFF8DYvNyY55X+E5FEUo1Vkipdux7L58PnOAAsfPxhvtK+HRm4e6A9D0T+6pj+3JOUneImBi2fj9d/9xsmLirkqXGjWdnUgxdpJPuBrCjHjTHYoRDvzZ6v1X8iklAKrJLUqIGDAHDS0wHIat2KkQum1WmbGmOMlphLs7OJqk1xI1mWheXzabZKRBJOqcAUYVlWxX6BsbapMYEAt/3kZ3zWvh0XrV1Pu/0HeA1oB6wEbgOCTTxukXgYW5DPJ8UlnDZuIh/7qv49GAoEcBxHxeoikhQUWKUQYwy7Nm2m8OFRUc9f9NJUDnTNIe2zz8CyeAS3v88rwFjgLuCZphuuSFwsAkq8FYAfDbiOo2XlnIhbgxgKBFk+c472ABSRpKFUYAqxLIvs7l0ZMGJIjXOtdu2h+3+XUnLj9Vh+PyPnT6X3CSfwqteCIR/o37TDFWmw+cDV3mM7MwMnM5MTTzkZYwy7N2/hiR/fReFDjyuoEpGkocAqhdjBYI26qXAb0O/8Ywxv/fpejM+HBbQuK8dufyo/fuwvQGX3dZFU8VRBPukx9v+zLIvTu3aJ+keGiEgiKRWY5NyWC4Dfx/KZ8yh86PGKc2eHrwG+OLUte879Kp2LVmEAjMEOBmOmDUWS2Qxgc0UD0OuqnFNNlYgkMwVWSax07Xo65eVihUIYfHylVw9at2/HkX37AfiKd50FdH/jbbq+/S5p5QEyPv+c7z4yhhPLyrnxr7/jqZ/dR2dQ93VJCVNx09ba/09EUpFSgUks3HLBpLnx76kdz6jSciHbu84A45fMZsKrhcx79C9s7fFNZv3pAT7I7sDR+x8AYBAwq+m/BJHj8kRBPm1qSf9p/z8RSXaasUohls9XpeVC+2otFxzbbSZqBwM83PtGnt1/gJeBkcD7wIQmH7FI3Y0pyCeUl8tH3aOl/4I4jq30n4gkPQVWKSZQVlbxy+XJGmcN23tcxOouZ8HNP2Uz0LPphyhy3MI1VQBORrT036tK/4lISlAqMMX4fD4s3JRITvVzfj8ArdufWucu7SKJtozYrUCU/hORVKPAKsWkZWTQa+AAbnv0z5wW4xpfRMrwtkf/3KTjEzkem4FLajlvjOHIvv3amklEUoZSgSkmFAyybPosFj8zkeHeMafaNcYYQuWBio7UIsno+YJ8NhaX0G7cRLafcEKVc8YYHNvmvbkLWDDmGc1WiUjKUGCVAozjuI1AfT6WTS2k8G+jATgxfL7GEwxgKlKGIsnmC2BsXi6fdcuhZEBfyhyHTBRQiUjqU2CV5Kr0svL5+Mpll1b0sgqX+NrVnlN99WC0DZtFEiVA5Q+ecJ+qcFC1e9NmXvztH9i5YVOihici0iCqsUpy1XtZtT+zc0VherlXmF49sHJsm0BZWY3tb0QSaUhBPotGDqUsxoIKy7I4vVuOtqkRkZSmGasUEzkbtfjsrtxyxz2Ue+eM42D5fOzcsInxv/i10iiSVDrl5bKmWw5r+vfhaPFHRFZVhcoDOEbb1IhI6lNglYKMMezatJmfePsAloWP425v49i2aqskaZwNrKfqFjUn9LwYcP8YCAWCFQst9MeAiKQ6pQJTkGVZZHfvylteymR+QT7gtlkA6PiVc9THSpLC3wryGTtyKJ/H+v/Qsihd9zGFDz2uoEpEmgXNWKWgUCDAshmzyfdSJp95HavD/Glp+NPSVLwuTWYCcB2wBzjPO7YEYFUxF/x7GuUnt+byUU/x9pB7Abh43ETOmzmXL774knuDwYSMWUSkMSiwShGRLRfemDiFhU89y7RY13pL1lfOXcj8MWObcJTSUk0CngIm4xapf6e4hEuffJa9b7zFCzNewM7I4IT9BzDGcOqGTXSZOpNzgkFaHzjIYmA2NfuxiYikIqUCU0Dp2vVYPh+W4/7qOe/qK2pN8VmWheXzaRsQaTJvA+H/0zrl5fLJgL5sv+RCiu66Ddvb++/LdqdiWRbd//NfPvjWpew/cJBPgY3U3n1dRCSVKLBKAdVbLpzeNYeRC6axZORQjkYJsEKBoFotSJP72VOPkXOa1wIkM4M223bQaVUxP/rxXQz86f/S/v0PCZSVcfSd5cx9dUnF87YDnRI0ZhGReFMqMAX5fD58WVmUDBzAgbO7At5KQCx8fh+v/PFhVs1dmNhBSovSC8g+uxtlrU+uOOazbbIOf8a/pzxHh5I19P2/EXQJBHn4wEG+TNxQRUQalWasUpAxhkBZGd8omEGf8KxUuNcCYAcCCRubtDxTgXfCH/gq23wc7XAaG666Atu2mf3JJxzas4/MAwcpBc6MeH5noLTJRisi0rgUWKUQX3kAHAfLshg3+D6ueuhxTvJqqHxp/op2Cz/+2x/VakEa3ZCCfOaOHMoPYvx/tvHKb3Nm0Sq2fbSG93//MGmOwz7cQvVbgAwgBzgHWNFUgxYRaWQKrFJE6dr1pH/xOSft2w/ACa1bx7w2LSODXgMHcNujf26q4UkL1Ckvl40D+vL8gmlsu/B8brl1MG0/3cLgq67na9Nmseqa7xF4Zxm/+On/42VgkPe8NUCBd78QuAetCBSR5kM1Vili1MBBPF6ylHLb3Rnwyrtu4+jaj2nlBVqRguUBlhfO1tYg0iiidVKfmj8Wy7IwxhAKBFheOIfFfW+JuSr1Ye8mItLcKLBKNX4/ADkXnMfzC6Zx7sx5US4yWFja1kbiblRBPucVl/D5uKpBuxXx/1rpWreTuohIS6TAKkX5/H5sv58PBw6ocS49M1Nd1yXu9gOT8nJZ3S2H1QOuq3LODoWwQyFtoiwiLZ4CqxRljCGtvJxzZ87lw1tuqnI8WF6uX3ASV24zD++xl/4D9/834zgVXf7VkFZEWjoFVqnMsgj/ujPGYFkWjm3zzx//jJ0bNiV2bNIsPFKQz0XFJXwxbiInHDxU47xlWRjLUpd/ERGPAqsUZVkWdmZmRSowXOPi8/v51UvPsWLmPF4bN5EjUYrbReqiFHg5IvV34OBhTok4HyoP4BhHs6MiIhEUWKUwXyDI12fMqpIKtCyL9Kws1VhJvQ0pyKd3cQmtvQL1cOrvlOzTAXBsBzsYZPnMOSx+ZqJmqkREIiiwSjHGcdzkn8/HhVNe4fJR/6pRYxUqD1T80hOpqyEF+WQUl3BaXi5ruuWwpv91Ua+zfBal67TyT0QkGjUITSGla9dj+XxYjttOceOV3+bzqF2v1W5Bjl+nvFyyB/QF3FkqOyuzyvlQIECgrIx3XpnOpPsfSMQQRUSSngKrFDJqoNu72qS5E42Hz+zM8wumVbkmMhWozutSV3b4PmLFXyRjDJ8fOszDvW+k8KHHlf4TEYlBqcBU5vNhZ2VVOeTYNqFgUAXFckxDCvLpVlzC7eMm4ouxyMEYA8CKWXNZMOYZBVQiIsegwCrVGQOWhR0K4U9LY8f6jTz3v0P0C1COqVNeLqFuOTzfvw9nL/lPlXPhgGrnxk28NOxBte8QEamjBqcCfT4fq1atYs6cOQDk5OSwbNkyNmzYwMsvv0x6enqDBym18PZn83lb3WxYVqSgSmrVi8pNj91aqizWXft9oLLh586Nm3j8xtt4/IbbFFSJiByHBgdWv/rVr1i7dm3Fx4888gijR4/mnHPO4eDBg9x1110N/RRyDJZlVfSx+vatt3DDyKG0jlrULi3ZkIJ8CkYO5dX27ai+rCFyr78tH36kgEpEpJ4aFFh16tSJPn368Nxzz1Ucu/LKK5k2zS2ozs/Pp3///g0aoNRkHAdsO+o5f3qaCtclqk55uewY0JfnF0xjxpOPVjlnh0Ja8SciEgcNqrEaM2YMv/3tb2ndujUA7dq149ChQ9jeL/3t27fTqVOnho9SKpSuXU+nvFysYAjjr3neGMPuTZspfHhU0w9OktJs4DpgNJWr/j79zrcAr+9ZIMjywtlq9ikiEgf1nrHq06cPe/bsYdWqVfV6/uDBgykqKqKoqIj27dvXdxgtTkXLhfToMbFlWXTo3pUBI4Y05bAkSU0uyOeEkUM5WktquHTtOrVQEBGJk3rPWF122WVcf/31XHvttWRlZXHyySfzxBNP0KZNG/x+P7Zt07lzZ0pLS6M+f/z48YwfPx6AoqKi+g5DqgmWl7O8UF3XW7pHgf8DRuflsr9bDiU39atyPhQM4ti22nKIiMRZvQOrESNGMGLECACuuOIKhg4dyq233kpBQQE33XQTr7zyCoMGDWLWrFlxG6xEF14ab1kWo2++g92bNid4RJIoQwry+X5xCf8zbiJ4vamciKafxhgc22HVvFeZP2asZqlEROIs7n2shg0bxssvv8xf//pX3n//fSZMmBDvTyGAvzyA4/dh0tIwxlSs6io7+nmCRyaJcg9ugfq6bjms638dbdetr3GNZVlYPot2nTsqqBIRaQQWYBI9iKKiInr06JHoYaSMIQX5dM8+jVM3fcqOiy+sOO5uwFzOipnzeG3cRI7E6KYtzUvkLNX4N+bGvC5UHsAxTkX6T4GViEj91Ba3KLBKUY+XLMUXDOJEacDqOA6bV33A03fck4CRSVN6AGhfshR/eQCMqbFxMnhNP43h3YIZCqhEROKgtrhFW9qksOpBlTtjFWD5TBWvtwT5Bfl0LC7hQ6JvnhwKBPGl+dm16RNtSyMi0kQUWKWgq2o5589Ix8ICq3pvbWkuHgaG4674O9AtJ+o1xhg+P3SI0QN/qhkqEZEm1OAtbaTpxUrwWZaFz+dT5/VmakhBPq+OHMq9ET2pnGozVcYY7FCIFbPmKqgSEUkAzViloPOBaA0V3KX0Nu/NXciCMWObeljSiMYCX+TlsrZbDmtjrPgL2/bRGgp+/3DTDU5ERCpoxioFdQBOWxtrKb2P9lpK36wEgZ97j+3MDOysTPZdcF6Va5yQrb3+RESSgGasUlAmcNvAQYwqWVrluB0MsXT6TBWuNxNjCvI5t7iEsnETOeHAwajXVKz4m1aoFX8iIklAgVUKijnNaKHC9WYiBDyRl8vqbjmsHtCXo0eOcELk+UAAX1qaVvyJiCQZBVYpKFbzMX9aGr0GDiD77K7qYZWiZgD9cb/HUNlG4YRMt2DdcRzsQLCipYZmqEREkosCq2bEGMOXnx1h0djnEz0UqYfJBfm0Li7h6LiJlLduFfUay7IoXfcxhQ893sSjExGRulBg1YxYlsWJp5zMT8f8jd/9z/cTPRypoyXAd3H7Uu3vlkPJTf0IAf6Ia6pvRyMiIslJgVVzYgw7N27ipWEPJnokUgdDCvLpXVxCj3ETwdvXMdyXKhxUObaNHQwp9ScikiIUWKU4YwxWuFjdsnj+3t9wcMeuxA5KjulNYGVeLmu65bCm/3WcFKMvleXzKfUnIpJC1Mcq1ZmqZew3/X4YrSM6c0vysYFvhx97fak+q9aXKlQeUF8qEZEUpBmrFNMHd8WY431s+arGxl/5n0sYuXA6Kwrn8tq4iRzxUkySWEO8nlQ/HDcR3779ODFaYoT7Ui0rnK3Un4hIClJglWKGefdTCvKjnrd8PtIzM9V2Icl0ysvlSLccnu/fh3MWvcGrnTvSJeK8+lKJiDQPCqxSzNe8+715udEvMIZgeaCi2FkSaypwIzCayp5Ua/v2pos3Y2WHQu6myd5qP81QiYikNgVWKab1sS6wLCyfpQ7sCRZe8XdpxIq/sPBiA2MMRw8cZPTAnyqgEhFpJhRYpZi6fMPSMjKUCkyge3BTf+6Kvz60K1pV5bxmqUREmi8FVs2QE7IrNuWVprUPOJWqqb89l/8P4M5QhQJBlqswXUSk2VK7hRQTuU+gY9uYyHYL3uPQF1+weNwk/eJuQq1wt6R5f+RQjtbS7qJ07ToKH3pc3xsRkWZKgVUqq74Ts1e7k3Fya0YunM4NI4eqp1UTWAR8hrug4KMBfRm/qLDK+VAwqJ5UIiIthFKBKcyX5m58UqX7ukctF5pGgKpvovCWNOB+XxzbYdW8V5k/ZqxmqUREWgAFVs1A9aAK3ALppdNmqs6qkVwFDCrI5z/FJfQcN5G1p59W4xrLW6HZrnNHBVUiIi2EAqsU0su7r54BDM9YGcfBb9s46ensXLte+8s1kndwvxej83LZ3y2HD27sBz6rSl49VB7AMU7Fyj8REWkZFFilkNFULV4Pi9yEOePwZ5Sd2pazvnoO6VmZBMvKm3iUzVs5kB7xsZOZUSWgcmwbOxiqaNCqmSoRkZZFxesp5OvefbDacTsUIlBWhmVZlJ/sthB10tPJ85b5S8OFV/295a36W3FW56jXWT4fpes+1so/EZEWSoFVCsny7l/09gl0bBuAT957n4d73wiAycgAb2PmW//xZ60MjIMHqFz1t3pAX8a9Wsh/Zkypck2oPKCVfyIiolRgKgmXqB/Oy8U4DpYXQC2dNivq7Ig/LU0rAxuoGDgv4mPbS/2F/yJR6k9ERCIpsEohkfVV4aAK4EcP/YHuF19Y8wnGYBzDge07ad2+HUeq7VknlSYA1wF7qAykJhXks6e4hPLRT5P1xRdkHTxEWds2YAzf/ftour79LsGsLCbefosWCoiICKBUYLOQnunuDViDZeFP8/PN66/htkf/3PQDSyGTgN4RH9vA/rxctvTqya5vnMuhiHYKXd9eyimfbuGZ6S/w+GWXcOWf/t7EoxURkWSlwCrFGWMIlpXzbsEMdm7YVOO8HQrxbsEMXhj6+wSMLnW8DYSTeA6Vb4zLn3iat4b+EstrxurYNl0Xv8nM09vz8DU38cikf9M6ZJOdgDGLiEjyUWDVLBgsLMbd/auIQ96+gZ8d0b6BdXQZ0PnMTiwZOZQj7dvR/fW3OHr6aez7yjkV11g+H2mbP2XGzPkV/6bbgU6JGbKIiCQZBVYpIlZzUMuySM/KotfAAdz26J8pXbs+fAKAzLZttG9gHQwBXgRCmZnufn8z/80lz+Xz7j2D3QsMBMvLeeeV6WxfvS6RQxURkSSm4vUU8QRu8Xq41UKYHbKxQ8GKDt9H9h/g8ZKllRdYlvYNPIbxwF0RHzuZGbTfspVTSndy2023gYFWu3dzww9u4G+Oww+AMyOu7wyUNumIRUQkWSmwShHh5qB783KBym1stn20hkn3D6811WeHbJZOK9TWKlH8qyCfnOISjo6bSFbEqsl9uWfzzH/mA+A4Dndc2ZcL9x9gPzAbuBd4GegJHAZ2Nf3QRUQkCSkVmCIyq30c3sam89e+wvd+cWeNNF+oPACO4z73wAF1Ao+iBCjzmn7uuOh8vmhzCm0/3cLgq67n6zNmVzT9fLdgBkcPHqp43nzgE2Aj7mzX/0vI6EVEJBlpxipFRNsjECAtI6NGmq907Xo2F3/It265CYwhdPpp/OSRB5n96JPqZeUpAc4FFuE2/Zz3+EMV5xzHwQ4EWV44uyK9Wljt+fc24VhFRCR1KLBKccHycpYXzqmS5hs1cBCAG1h5M1vnf/8qzrvyClbMnMdr4ya26ABrNbCyIJ9dxSVRz1uWVbHfn4iIyPFQYJXCjDFg3FYL4QAqFn9amra4AZ4tyGdHcQl783LZ3y2nyrlQMIRjhyoWAoiIiBwvBVYpLLLVwjGDJWMwwK5Nmyl8eFSTjTGZLAPeyctltRdQOZkZgBegAns/3cKUYX+M2mhVRESkLlS8ngImEb3GyrHtiuLqY3ZWtywsyyK7e1cGjBjSOANNYlOBS7zHthdQhVnev02HFvpvIyIi8aMZqxTQ37sP97BybBuf38/Wj9Yw6Ve1t1qI5Ng2705teW0XHgZurOW8MQZjDO8WzGhx/zYiIhJfCqxSQGvvfl9eLsZxKlotLJ8xp25BlTHuhsy2wxsTXmxRbRd+AnQuyGdJcQkXjasaNIVTgDs3buKlYQ8qBSgiIg2mVGCKsXw+LJ/7bbthxNBat6qpvr2NyUjngXkFLWZ7m2zgBdymqh8N6Mtzr86oOGeMYefGTTx+4208fsNtCqpERCQuFFilgFg9rNIzMyr2CIwm3HYhUrjvVaznNCc7cP/twC1UT8twa6scx6Fo1jyevft+BVQiIhJXCqxSVLguaPfxrvIzhqVTZx672D3FTS7IZ8nIoRyJMjPn8/m4+PprW0RwKSIiTUuBVYo6npVsofKA+8CrtWqTffox+16lsnLc9N/qAX0Zu2B6lXOhQKDuKylFRESOk4rXk9xPcNNZTrXjjm0TCgaP2cyyyvY2XjD1tW/1YuSCac2yC/tWIN17bGdmVPwPbozB2A6r5i9i/pixLaqAX0REmo4CqyQX3lRlSrVWC58Wf8TkISOOGSBU2d7GY/n9pPv9za4L+6NA5xjnLMvC+Czade6ooEpERBqNAqskd5p3vzfcasFbEfhuwYwGBQihQJBlM2Y1m75N2UAHr63C16u1VQgFgzi2ra1qRESk0SmwSnKRKwLDQRXAzX8aQdcLvnFcqTzjOFjGgN/Pyas+aFabDO8ARnv7/626oW/F/9ihYJBl090AUjNVIiLS2FS8nqLSMzOPq21C6dr1bg8s2wFj+OKSb3JG7tmNPMqmESKiK31EWwXjOKya9yqLx01SUCUiIk1CgVUKqk+rhXCtlclId4vYfT5+/crElG8WWor7P/HevNwa5yy1VRARkSamwCqJ9YlxPF6bBvvT0lK6WegY4IwY54wx2KEQ782er7YKIiLSZFRjlcSexa2xsqsdt0Mh7FCoYcXYXk+rtW+9y9QH/9bAkTa93xbkc25xCUfHTcSJUmNmWRaWz6dVgCIi0qQUWCWxDt59frh+yHHw+XysX7qCV37/UL0ChlB5gLTMjIrA6ptnd2VqCjYL7ZCXy+puOazu34cP3lnOeRHnQuUBHONoFaCIiDQ5pQKTmA93ReChcKsFLwBaNPb5egVVpWvXs6xwtvfi7re+rFNHRi6cnlK1ViHv3s7MwM7K4utXfhtwi9WDZeUsK5zNw71vpPChxzVbJSIiTUqBVYqwfD63yaUx/L/n/1WvQGjUwEE1WyxY1nGvMEykHdT8nzYccGJZlK77WAGViIgkjFKBSS7cRiDMsizSszLj2zXdGFYUzmXhk+Ma/lqNaFRBPquLS2hVrQGoMYZQeYDlM+co9SciIgmlwCpJ9fLuq7cRqOsegcdSvdbq4nO6sTCJa63OBkxEXVWYMYb35y9i9qP/1CyViIgknFKBSeoV3BWBNVgWHyxc3KCml1VqrbxgKu28cxm5oGqt1QRgN1AS8dx/AGuBYmAGcErEueHABmAd8P16jSy29d59uK4K3KBq/dIiZj/2pIIqERFJCgqsklTHGMd9cWh6GbPWKqtqrdUkoHe1574GfB04HzfYecA7ngfcApzrPedp4vc/1+SCfJaMHFrjuGVZnHPpxSlRGyYiIi2DUoFJKrwisLpgWXnj1RIZw4rCOSx88lkA3ga6VLvktYjHy4CbvMf9gJeBAPApsBG4xLumIXYBU/JyOdAtp8rxeKVERURE4kmBVQowxmBZFqFgkCd+fBc7N2yK22tXr7W6+qtfqXOt1Z24KUuATlQNorZ7xxpidEE+JcVuItLOzKg4boxh9+YtTPntH+L6byEiItJQSgWmgHA7AZ/Pz69eei5uPaei1Vod/dpX6tTXagRuP6kpDR5FdFcBTl4uqwf0rXHOsiw6dMtp0HY+IiIijUGBVRKahFu4Xr3Vgs/vIz0rK249p+rb12oQcB3wk4hjpcCZER939o7VRysqU46RM1XgpgCDZeW8WzBDewCKiEjSUSowCd3s3VdvtRCXPQKPxUsJml27KXx4FBnVTv8A+C1wBfBlxPHZwEvAKNzC+3OAFfUcwmfEWBGJ2yg13ARUREQk2SiwSkLVg5lIDW21EEtFrZWXEvSfkc3irl04Y8cuWn3+OduAP+KuAsykckZpGfC/wBqgwLsPAfcATj3GMbkgnyXFJfSs1gTUsR1CwYCK1UVEJKlZRF981qSKioro0aNHooeRNMIByeiSpTXPOQ6bV30Qn47rniEF+Wwu/pBv3XJTjXON8flisYExJUvxlwcI+nz40tMwxmAHQyybMYvFz0xUvyoREUm42uIWzVglqer1VY7jEAo0zozNqIGDAKoGVl5K8IQ9eyl8eFRcP180QSrTf3ZmRkXxn3EcVs1/tVFm6UREROJNxetJ5g+4AUa4vsoYd0Jx5/pNPNz7xkbfYDhUHnAfeCnB8g6n838vPx+3lYjR5Bfk8+bIoRw5/bQa53x+f4MbooqIiDQVBVZJZni1j8OtFjp0y+F7v7iz0YIbqNZ+oXIAWBkZ/M/NN/DTMQ/H/XPawL68XD66oS/jFxVWORcqDxAoK9MKQBERSRkKrJJMZozjaRnpcWuzEEvU9gseCzjrq1+Ny8zVkIJ8bhg5lM/at6v4H9DJyMDy+wF3ls4OhVi1YFGTzNKJiIjEi2qskky01QTGGELlgcbbyiaKilWCFQOz8GVmcNnNN9Ap7xyevPXn9X7tTnm5nNUth+f796Hj+x/WOG9ZFpbPR7vOHRVQiYhIStGMVSow7n8srIrap8YUNSUYIefr53LzX353XDNX4Vmqg95z7MwM7KwstvW6pMp1Sv+JiEgqU7uFJDIF+DFuu4UxTdRqoTaPlyytOXMVZgyUlfHYrXezc/3GqM8fUpDPp8UlvDZuIg++MRd/eQCMwc6qmfA0xmCM4d2CGWqrICIiSU3tFlLED737F6q1WggFgzi23eTNMUvXro/Z3wrLgqwshk6bjC8Q4OAbbzP6kTEMfnpURTDVKS+XM7vl8O3+fbCpuT0NuF+bz+9n16ZPeGnYg9pUWUREUppmrJJI9cag4VYLq+a9ypzHnkzYLE545soxDhlZWdEvMsa9+XxYoRCWMTjp6bW+rjGGz/buY/TAn2qGSkREUkZtcYtqrJKYZVlgDN+4+juN3mqhNuGaq4d73xj7IssCn/u/k0lLqzWoCq/6WzFrroIqERFpVpQKTBIXePfVO65bPh/pWVn0GjiA7LO7Nll9VaRwZ/awmHVXx2CMwbFtVs5dyPwxYxVQiYhIs6PAKkkspmrH9TA7FHJnd5Jk8+HIuqtjpgepDKbKjn7O6jffVkAlIiLNmgKrJNG2lnMfLFycNHvlhWevup7/DTYXf8jiZyby4JvzqgRZoUAAx3EIfPkla/7zjoIpERFpMRRYJYlYqwj8aWlcfP21tOvcMSFpwFgi04PhWazFz0xk8NjRFY8VTImISEujwCqJObZNKBhMmjRgLJFBVvV6LBERkZZEgVUSKMGdsQr3r3JsB5/fxyerinnxN7/XzI+IiEiKULuFJPA1735vXi7GcbB87rY1r/5rvIIqERGRFKLAKglEzlZZPh+WZWGM4e5nRnPDyKEJ618lIiIix0eBVZKo3mbBsqyK/lW3PfrnBI1KREREjodqrBJsGe6MVXXVm2mKiIhI8qv3jFXnzp15/fXXWb16NR999BH33XcfAG3btmXRokWsX7+eRYsW0aZNm3iNtVmKtUOiZVlYPh/tOndUnZWIiEiKqHdgFQqF+L//+z/OPfdcLr30Uu655x7y8vIYPnw4S5YsITc3lyVLljB8+PB4jrfZida/yhhDoKyMdwtm8MLQ3ydiWCIiIlIP9U4F7tq1i127dgFw9OhR1q5dS6dOnejXrx/f+c53AMjPz+fNN99UcFVHdiiEPy2N3Zs288zPfqmZKhERkRQTl+L1Ll26cOGFF7J8+XI6dOhQEXDt2rWLDh06xONTNEvbcGesXizI5+jBQxw9cAiARc88r6BKREQkBTW4eP2kk05i+vTp3H///Rw5cqTGeWOibdQCgwcP5u677wagffv2DR1GSuro3e/NyyUrEMCfng7Aro2fJG5QIiIi0iCmvre0tDSzcOFC8+tf/7ri2Lp160x2drYBTHZ2tlm3bt0xX6eoqKjeY0jlm+Pd9nXLMXu7dzWvD7vfPFb8jhmzeJb5oGsXs9HnM4vAtEmCseqmm2666aabbu6ttrilQanACRMmsHbtWkaPHl1xbPbs2QwaNAiAQYMGMWvWrIZ8imarV8Tj/Fn/5t9TxnPBy9Npt3kL/zOlgMN9r2HUhCdZAqhCTUREJDXUOxV42WWXcfvtt/Phhx/y/vvvAzBixAj+/ve/U1BQwF133cWWLVsYOHBg3AbbnCzBra3qUFwCQPCkk9jfNYcTduyk25K3+G3/a5k69PecBLyJgisREZFUUO/A6p133sGyorW2hKuvvrreA2opsnBrq3Z3y8EHnFy6k9PXrWfO5i38YNt2nv/nOACOACr/FxERSQ3a0ibBfJkZpH/xBX1//QBv/OY+vszIqHGNScC4RERE5PgpsEqAlVRuY+MLhuj76xGs7fMDNn3/SnoNHEB5h9PI9s5nA3sSM0wRERE5TgqsEuCC8ANj+P4fH+JAty6svP0WguXlvFswg5cPfcYg75JBgMr/RUREUoM2YU6A8DY2Hd//kK/NWcjec7pz2w8HYRyH0EXnM/rEE5hQVsZdwBZA5f8iIiKpQYFVE7sn4vGOi85nVMnSKuczHYc+va/i6jvuQURERFKLAqsmNga3zcLpXpuFsFAgiOPYrJg5l8XPTEzI2ERERKRhFFg1MT9um4Wd3XIq/vGN47BsxiwWPzNRewSKiIikMBWvN6HIbutpmZVtFRzHwcKCGH3BREREJDUosGpCb+CmAavzp6XRa+AAbnv0z00/KBEREYkbpQKbUAZuGjCSMYZgeblqq0RERJoBzVg1kewYx40xfLBwMYvHTVJ9lYiISIpTYNVEPqGy23okn8/HxddfqzSgiIhIM6BUYBPJouaef0oDioiINC8KrJpAeDVguHDdsW18fj/bVq/l+Xt/oxSgiIhIM6FUYBN4EzcNuDcvF+M4WD73n33m30crqBIREWlGFFg1gXQq04CWz4dlWRjH4X+fe5IbRg6ldft2iRyeiIiIxIkCq0b2kxjHLZ+P9Kws9a8SERFpRlRj1cgmE2tvwACO46hwXUREpBlRYNXIwrVVkXsDOrbNshmztTegiIhIM6NUYCN6M+Kx9gYUERFp/hRYNaLLib43YFp6umqrREREmiGlAhtROA0YybFtQsGgaqtERESaIc1YNZLPiL6FjTFob0AREZFmSoFVI2lFzS1sAPxpfu0NKCIi0kwpFdgIJsU4bodC2KGQ0oAiIiLNlAKrRnAbbtF664jeVcYYls+Yw6Knn1MKUEREpJlSYBVnrajau8pvDJZlUTRzHtP/8o9ED09EREQakQKrONtHZdF6ZO+qC6/9HsHycl4bN5Ej+/YnZGwiIiLSuFS8HmcZRC9aT8/MVO8qERGRZk4zVnG0Abe2Krv6voDBEI6tonUREZHmToFVHHUHZuflsrdbTsUx4zgsmz5T+wKKiIi0AEoFxsl4Iraviaitsm1b+wKKiIi0EAqs4uROam5fA9oXUEREpCVRKjAO+hBr+xqDY9usnLuQ+WPGNvWwREREpIlpxioOZhM9sLIsC8vno13njqqvEhERaQE0Y9VAvXCDquotFrR9jYiISMujwKqB/otbtN6h2vY1RTPnsfCpZzVTJSIi0oIosGqAC4i+fc3SabOY/udHEjw6ERERaWoKrBpgJTW3rzHG0OP6azC2re1rREREWhgVr9dTrNoqy7K0fY2IiEgLpRmreopWWwUQCgRwHEdF6yIiIi2QAqt6uIeqtVXhf0Q7FGLZjNnavkZERKSFUmBVDz0L8lnizVRF1lY5IW1fIyIi0pIpsDpOk3Bnqg5EbLQMXm1VlltblX12V56+455EDE9EREQSSMXrx+l2796O2GgZwLFtgmXlvFswgxeG/r7pByYiIiIJpxmr47C7lnOWz0fpuo8pfOjxJhuPiIiIJBcFVsfh1YJ8zqi2CtA4DsFAQKsARURERIFVXdnAmLxc9kfUVhljKJq9gPljntYqQBEREVGNVV0MobLDuhNRW+XWVZVpFaCIiIgACqzq5LEYx/1paeqwLiIiIhWUCjyGz3A7rFevrQoFgzi2rdoqERERqaDAqhZ9gFa4fat2d8+pmN5zbJtl02epw7qIiIhUocCqFjdHdFj3ZVR2WLeDIXVYFxERkRpUYxXDPtyZqtUD+lY5HtlhXbVVIiIiEkkzVlHcA5zqPY7WYd0Ohlg+c45qq0RERKQKBVZRPFnLOXVYFxERkVgUWFWT79VV9RxXdTbKsW1CwaBWAYqIiEhMCqwivAUU5eVysFsO7w+4Dr933A6GWDp9plYBioiISK1UvO65CfiW99jOzMCfmQmAcQwr57/K4nGTFFSJiIhIrRRYeQqo3LYmkuWzuLjvNVoBKCIiIsekVCAwOUZdlbqri4iIyPFo8YHVZ8D4vFwOdMth1Q19K/5BQsGguquLiIjIcWnRgdXHuFvWgFtXFf7HcByHVfNUVyUiIiLHp8XWWD1ZkM/WkUM52r5djXM+n4+Lr79WdVUiIiJyXFrkjNUQIJCXy+puOazuf12Vc6FAAMdxVFclIiIix63FBVZXARcU5LOXqtvVGGMwjsOq+YuYP2asUoAiIiJy3FpUKrAX8Bru5srVWZYFlkW7zh0VVImIiEi9tJgZqwuAd4jeq8oYg2PbrJy7kPljxjbtwERERKTZaBEzVsML8nl05FA+b98OO8p5y7KwfD7NVomIiEiDNPsZq6uA0yoK1fuw9dOtdIo4HyoP4BgVq4uIiEjDNevA6ifAC8BoKgvVO33Vra9yHAc7EGT5zDlqAioiIiJx0WwDq0cK8rmouISj46LPQlmWRem6jyl86PEmHpmIiIg0V80ysJoE7I/VpyoYwrFDSv2JiIhI3DW7wGoRcDVV038Q0adq3kL1qRIREZFG0axWBY4ryMeKsU2N+lSJiIhIY2s2M1ZbgGnh9N+A6um/II5tK/0nIiIijapZBFb7gbbe4+jpv1eV/hMREZFGl/KpwEkF+axS+k9ERESSQErPWJUDT+XlcqhbDiUD+lY5FwoEcBw1/hQREZGmk7KB1eSCfN4qLgFqpv8c22HV/EVK/4mIiEiTSsnAygbG5OVyoFtOjXPuvn9K/4mIiEjTS7nAyqayMCxypgrAsW3sYKhimxoRERGRppRSxeuTC/J5feRQjkQpVAewfL6KbWo0WyUiIiJNLWVmrBxgdF4u+7vl8MFN/atEhE7IJhQKqlBdREREEiolAisHsMKPMzMqgiq3UN1m5VxtUyMiIiKJl9SpwCEF+bw2ciift2/Hl61b1TjvFqr7VKguIiIiSSGpZqx+ADwB+IEXgFMitqj57MsyToq4NlQewDHqUyUiIiLJI2kCKx/wL+B7wCHcbWryN23mQPeuAJyUmQnUXPmnmSoRERFJFkmTCrwECJ3/dS4ZOZQt7dthAd3feKvGdVr5JyIiIskqaWasOgGB7l3pNaAvz/e/jm/mv0Tr3XsrzmuLGhEREUl2jTJj9YMf/IB169axYcMGhg0bdszr25zRgWyvON3OzMDOyuRIx2wAHMchWFbOshmzebj3jZqpEhERkaQV98DK5/Pxr3/9i2uuuYavfe1r/OhHPyIvL6/W57Rq04bLxzxC6117Ko/t3sORDqdhWZZSfyIiIpIS4h5YXXLJJWzcuJHNmzcTDAZ5+eWX6dev3zFGYbHjom/QZss2Tt6+A18wyFfmv8bHvS7hnVemM+n+B+I9TBEREZG4i3uNVadOndi2bVvFx9u3b6dnz57HfJ5JS+ONEf/Hjb+4H8u2Wfn9Kxlyz1DNUomIiEjKSFjx+uDBg7n77rsBOCU9kx93/zp0+zrlP72bzw8dpu2evbz+v79K1PAEaN++Pfv27Uv0MCSCvifJR9+T5KTvS/JpTt+TLl261HrexPN26aWXmoULF1Z8PHz4cDN8+PBan1NUVBTXMegWn5u+L8l30/ck+W76niTnTd+X5Lu1lO9J3GusioqKOOecc8jJySE9PZ1bbrmF2bNnx/vTiIiIiCSduKcCbdvm3nvv5dVXX8Xv9/P888+zZs2aeH8aERERkaTTKDVWCxYsYMGCBXW+/tlnn22MYUgD6fuSfPQ9ST76niQnfV+ST0v5nli4OUERERERaaCk2StQREREJNUlPLA63u1vJP46d+7M66+/zurVq/noo4+47777AGjbti2LFi1i/fr1LFq0iDZt2iR2oC2Qz+dj1apVzJkzB4CcnByWLVvGhg0bePnll0lPT0/wCFueU045halTp7J27VrWrFnDpZdeqvdKgt1///189NFHlJSU8NJLL5GZman3SgJMmDCB3bt3U1JSUnGstvfGE088wYYNGyguLubCCy9MwIgbT+KWJPp8ZuPGjaZr164mPT3dfPDBByYvLy/hSyVb2i07O9tceOGFBjCtWrUyH3/8scnLyzOPPPKIGTZsmAHMsGHDzN///veEj7Wl3X7961+bKVOmmDlz5hjAvPLKK+bmm282gBk7dqz5xS9+kfAxtrTbpEmTzF133WUAk56ebk455RS9VxJ469ixo/nkk09MVlaWAfc9MmjQIL1XEnC7/PLLzYUXXmhKSkoqjsV6b1xzzTVm/vz5BjA9e/Y0y5YtS/j443hL3CevT88r3Rr/NnPmTHP11VebdevWmezsbANu8LVu3bqEj60l3Tp16mQWL15svvvd71YEVnv37jV+v99AzfePbo1/O/nkk80nn3xS47jeK4m7dezY0WzdutW0bdvW+P1+M2fOHPP9739f75UE3bp06VIlsIr13njmmWfMLbfcEvW6VL8lNBUYbfubTp06JXBE0qVLFy688EKWL19Ohw4d2LVrFwC7du2iQ4cOCR5dyzJmzBh++9vf4jgOAO3atePQoUPYtg3o/ZIIXbt2Ze/evUycOJFVq1Yxfvx4TjzxRL1XEmjHjh089thjbN26lZ07d3L48GFWrlyp90qSiPXeaM6//xNeYyXJ46STTmL69Oncf//9HDlypMZ5Y0wCRtUy9enThz179rBq1apED0UipKWlcdFFFzF27FguuugiPv/8c4YPH17jOr1Xmk6bNm3o168fXbt2pWPHjpx00kn07t070cOSGFrCeyOhgVVpaSlnnnlmxcedO3emtLQ0gSNqudLS0pg+fTpTpkyhsLAQgN27d5OdnQ1AdnY2e/bsSeQQW5TLLruM66+/ns2bN/Pyyy9z5ZVX8sQTT9CmTRv8fj+g90sibN++ne3bt7NixQoApk2bxkUXXaT3SgJdffXVbN68mX379hEKhZgxYwaXXXaZ3itJItZ7ozn//k9oYKXtb5LHhAkTWLt2LaNHj644Nnv2bAYNGgTAoEGDmDVrVqKG1+KMGDGCM888k65du3LLLbfw+uuvc+utt/LGG29w0003AfqeJMLu3bvZtm0bubm5AFx11VWsWbNG75UE2rp1K5deeiknnHACUPk90XslOcR6b8yePZvbb78dgJ49e3L48OGKlGFzkNAir2uuucZ8/PHHZuPGjWbEiBEJLzpribfLLrvMGGNMcXGxef/99837779vrrnmGnPqqaeaxYsXm/Xr15vXXnvNtG3bNuFjbYm3K664oqJ4vWvXrmb58uVmw4YNpqCgwGRkZCR8fC3tdv7555uioiJTXFxsCgsLTZs2bfReSfDtwQcfNGvXrjUlJSVm8uTJJiMjQ++VBNxeeukls2PHDhMIBMy2bdvMnXfeWet746mnnjIbN240H374ofnmN7+Z8PHH66bO6yIiIiJxouJ1ERERkThRYCUiIiISJwqsREREROJEgZWIiIhInCiwEhEREYkTBVYiIiIicaLASkRERCROFFiJiIiIxMn/B6WJzn5Q+mQ5AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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W6GtifjMgyHOyBSCo9ZBNf2PeFQJ6FHiV/F7EodayWXqEjAdgGrsjgT9G7NclAB+hDKtON3tKBwmAPbKqaXz7WOvq57HVSteYz2WUAJjfZLaNp2lgIVPwixKAE1Ge1FZU58u4XIt6P2b4y9tRjU/OIVMX0GgcyzT65nuXFBUnAK4bbBuS3o51INoD0A9V2LjzpiEutACYHkXcbQegHrTDUKUSs1T8LKqi0DT6fYx5nf5p29NNBfO+VZEx0kGdvyC7s4+rki0q3GaG5czt4ngApmjoe3QqqqR+QcD2YZgCYA8/AdlhTVClUVB1QGG4BOC/UIZVp5tNqKMEQFf6mh6ALQAug23Ou5rzBpX67Q/ymPSx0nUe9TUbQcYLMbf9CerZeRLV69weGcDF/sB/Bx4iu7PbTNS9+Bmqs2YTmfdJG2RTAJIcQqRiBeAdggXAfjg1UR6AxhVasEMxevyYfIx2mFHS+3IdL2yf3wN+a+V9EKpZmvkgmi+QPUrovqhRVNPCvm/aszPvjW2Ydzr+c1WyxbkHcQTAfDZqjPlqVAiuO8qwTgrYPgy7Pbl5bzqRCdPoZ1h/ZOStiP2aAlCFEqjFVnqQAOw00rRx1R3DzPwEeQC5CkBPYz5KRCD7GnUm86yY12i1P68N70jUc30/8DVUf51ryK5bcPET1H24y0r/Der7Gv1Rleu7cRc8JQSUACNQSv42uQtAkAdgG/yw2LI97UpbAcinH4Be7kJu9Qhm2Kob2QZLexZRHoB+URai2pKnhb5v2jC5PAD7XpgCENbVPs71M7dz3XPIfsHsuPk4fx+/J79vLdgl7j7WvFmaBNUEeRuZVkJBmIZ+sD//rpVui08NqkDwjpGm708VbVv9BAmA6SWZlfRBAqALIeZ3mM131tyfXYBxvefDyQiATrvQn/7Wn34f+IU//TluTkENHXIP2a2wQNmfs1D3/Hky19UWAAkBJcAIVKePT8l+yD9DtT22b4RpEKNaAWlcpcE48fv2hID0NFfDb6Z3Iful60zbB9HlAZgvD6Q3BPYgVFvtjwkWAPteuFo87aQt2nCEXUeXN2HGsM26BWgrAAejhm1+FVUazHXc94HGvH1vXJ3RDkQVfKIwDb2OkdsCcACZtuvVZMToHSNtgDFvf4wnjgcQVJdjCoCeNws9QR6AWYlbTdse2/uhnulVRhqoprPvk+k7AMoD+CWq2ewvyBaaL6HCPKsIri/4EBX6AbcA2EOKJ0WS+y5JhqA6Y9ilnA2oUoxdMqgx5s2XylzHrhDMxQMwBcAu+duloqqAqf6/G/EMl7lvu07CPpcuuD2AKivdfunSGOLXvm8uAbCberpK+2HtrO1rbDbjdYWAzFKpaaCgrQDUoGLDi/20UahnMy6mAHQn24i6BOAgVAewKFyhHpcHsBZVqRwkAH0d83pZ3yO9T5fxrjHmze1dAhC3HsEMbdl50oK1zkgDJdSracvVqALF91HNqR9DXfd/QxUoLwQ+cWxn04J6vvQ12UZ2SFM8gALSD1XSNx/mIShDYirxbmN9TdzWJXHqAOySt/kAR41nEoa+oXHDSHazVPvYdmVUkAdwuLVNGmgBsENAYV+YcpX28+loYwuAvu5mmt1ZzhaA/ijvZQlKMIM65wVhDv5W40/34BaATijvNyr+D24PYB1tBUB7E6YAvGukmQJgl/hNY2dW4AcJgDmvjf7nRAuAWQDQLbJ24BYlfc0+NNJA1QG4BADgB6jGEx+iOnp+FxXWGYsapjwOtgfQjISAEqMvKmzg8gB0Wh8yPQVrjG3Nlyoo5gvucEBQ6d4M2yRxM2yPIKpy2C4xm7F+s5RiP6BmDLs9ApYLg1Guub5vrs9AQnYoplACELTdzoB5cAtAM8ogvUn0R2hsBpJp1aSNWzPZY+noYw1C3Vs7Hu3CFoDNfh51eg3qGut96fAJZMbUiSMA/yC7ZRFk9x6uCZjXhtKuV3CFkczrYH7kySWSLgHoizq3sC+szUF17OqNeo8uIreh2O1K4GZEABLDJQCDaCsAzf5/UU0/NbuN+bDYcpTBTYq4QuAaME0/iH3IhERsYbAr0pOmE6qZ3QaU0JqlSNsDMO+DawiLYgqALmisIrevrHVGdQRb7y+bAmAas0/INtAfxNi3LQDvWum6tG8KQF/U+X5qpel5LQCfGcvbadvk1Lx3Nca8Pp89ZDd3dXkAQSJiC4A+1ocEC4DuTBfkAZjsIL/QZ5AHoJcPBP4vqm6h0FS8APRAPThbyb4RuulajbGtKQZhlYtxmhemVUq2CaojsAXBXF//V2Ok23HWoP+Sohb1omvh7kLmxbfF2TTEudYBhBG1L1tszE5h3cj2NNegYvRxu/3XogygLnEHlW4/Ivv+NMfYdwuZa3kAbQVAC9kmf6qPt42Mt9UVdx2Azk+QAJjXyHzfdP7tuL9LAEwR6e+YD7pG5rLeZy4CkC8tZDdJbSbTTBxU44r/RduOf4WgogRAl1pNAajx/9tGtgewHVWqD/IAbEwjE+YBlApBdQQuD8DVS9gWAPNFS0PctMehQ0C9yDzM9jmYhth1T/K9T1EegH1c85rV+lNTAHrQtvdsELoC2PYAPkZdB738IdkhoeYY+9ZGXHsZm4z0LrhLyv3IvFeQbbBND+Bjst+xVrKH7qgx5vs70lsIFgAtWi6jb843W8u2AJjnpXsvm8NFFxp9zcz8ucLN5pAehaKiBEA/hKYA6AttCkBvlOvcQvYD6fpYiiZu88JSwxUKMvNtCoDpWvey1qmxlpNGC4D2AMLqZ8LCMkFpcchVAEz0OD5aAHTl7EExj60rgF0hIFCd8najjKxd0IlCG6Qu/nbbjPSwWLnpAWgv4SOy645sAbDfsah5O+yj54M63Jnz9jXaBxVS0hXR/VBG1gxj1RjrJIUpmi3+8c1nWASgQOgSfJQAmA+naVhsAYiqXCwHAdAPQFD7dlfLIGg7XlKNtZw0uqSsBSCsX0aadQBmmj7ubtr2CdAC0OxP1/jTuPUAYR4AKOO2jUwFYz4eQD9/22Yj3dzXVn/qCgFpAdAiUeNPXSEgV0k/aN4u9fcOWZeAfZvXaDuZimh9DpC5bjV+WpKfrTQF4BPaPiv6Hd1N4akoAXB5ADV+WjPZAqBvRFiv0h0B85pyEACNDgnZHoCrUxu4KzTN5aQZjCqZbaStUNsPdZp1AC5vYxdtX2o7BLTOXy+uAGgPQIcmavxpsz/dl+xCjf4/zkdOdF61yOt9mkYRwkNAelsdT9/H3153wExSAIL2FySSprDZ3o5uqZUkZghoO22fFU2H8wCuu+46li1bxtKlS5kxYwbduiXbJiauB9CbzI0Iu0BRApCvYSkmtgAEhb1cnZqa/eW06gA2oWLItgBodBPJqBBQvvcpyuuL4wFoY9SK6kQVNwQ0EGVMm/1l27jZAqANtDkYXhA6r1qkmo10va/PyB73JywEpPOn69Xsd6zGOHaUGJgduHqSCUu61rX3p/NkXiPTFuhzgGzhbCZZTAFweQCaDiUAgwYN4pprruHYY4/liCOOoKqqissuuyzRY8YRgG6o+HaYEms6kgegqcJdoW1jl/j7kxn1MS0PQJd+zYpBTSsZwx5VCZxECMg0+rto2zzQFgBQYaBcPIBNZMIC/VHGXZfwXR5A3Di2LQCuOgAdFmnF7QEECYArzFpjHDto3tULP6jJaNB8f9SzoO/RPrS1BS4BMO9REuh7WEO4AHS4EFB1dTU9evSgqqqKnj178v7770dv1A7iCIDZftp1I8wX2RwHv1zrAFy4BMAufXS11ulNugKg+26Auie217GbzL2KqgNIohLYPL4rBBQkALl4ADr8BZnSozYSLg+gOea+g0JArn3pJqNRHoBpbLujSu8uL7vGmDcNvOs7y0HfXnZ1/tLz5nvdn2gBSDMEVENbu2N6bB3KA3j//ff5j//4D9577z0++OADtm3bRn19faLHtAWgCnWDdc27GY/UTdRsgkr9HcUDAPcQBzsC/odMSVELQFohIF1ccAm1aXTD8h6UFoe4AmB6A2bpeqe1j7dQRqiWaAaiPAA7fqyPWUgPoNlIt/elC02diRYAu8T/CW3fsSCjbo9Sa07DtrP7BJievR0CCvIAmkkWWwCCCpkdSgBqamo4//zzGTFiBIMGDaJXr1587Wtfa7PexIkTaWhooKGhgdraOK9GMPphcD0EkC0AQR6AeUM6qgC48m2en/0FMF2aTcsD6IIyTmECYJfAXfUBmjRDQPra7UNbw5JLS6ABuD0Asw3/Z7TPA4gKAek07Sm4QkDaw7FDQJAZXsLEZej1+cTF9E5tz8C8RqYXYp+XDm3VkHwIyGx1Zdsd813rUCGgcePGsXbtWrZu3UpLSwtPPfUUxx9/fJv1pk2bRl1dHXV1dWzdutWxp/hoATAv8r5kl3BcIaAg4ycCoNACYDYLBPgpcF8B86XRwxqYHZRsTAMcFA7SpOkB6Gtn17VARgCiwkDVqGtuCkAfMl6smb/2eABhISCXANgewCdkrpEZbrHzZ1Jog2QWRno6jrkTdZ90GMssDOrQZnOB82Rj58dcNt+7DuUBvPfee4wdO5YePVSU+bTTTmPFirjj5+WHHoDKI/shNx9mjXkjzE8eBhn9jloH4EqzBcAVAhqKGinxOxS+C7tuA7/Rn7pipkECUEihDrtOZgjK5QFAWwF5B5X/KA9AC65ZCaz3FyQA+XoAZpgqVwEwDX4v1HtkhjdcApAkXWlbIa/vkxnGwk+zQ2BJESYAHTYEtGDBAp544gkWLVrE0qVL6dy5Mw888ECix7QVHtRNdgmA+XDGift3lGagUJgQ0NXG//+zQPnShAmAzpv5optikNZYQEEeQFh9xC7U9wCiPADz/MNK1Nq42T16o3C9GzrdVQnsCgF1p21LuqD85YNpxOM0bQ3Kg17WDdD1R27M80orBGTmR5N0CCiNBhuB3Hrrrdx6662pHa8v2TcY1E1+20qDbCXeiXrIdFxVU6khIPtc9Ytidgw6CmhEhQG+CtxSwPzpTlCuENCnZL7noAdWiwoBpdEKSL9oUSW6tWS+Wx2Eef5hxuNzPw99ye7RG4UpAM1Weg9Uad7sMatDcqYHAG1j/EHG11zfbna8m0yjgs/IxPQ/I3uE0d7GPruReV9tbNH5nOxGC/r+tdC2t3ZSuO6Z5lNjnSR6I1dUT+CeZF9QCA4BmQ+nOR9XAFrIv3RTbKKMpHmun5B5gcxPBOpKytdQH4spZBc/XQJ2CYC+P0El8DTrAFwhqLAQEKjCyIGOdJMwD8AVYtFGM04vYMh+N5qtdDPco9PM/edi8IOMXZC3mcu8eZ/tppRReYLsEFBa/QBc+TE92iSoKAHoRuZCthhpZmlGY94I86ERAQh++T7xp13IdFRa6C8fWcD8DUS9lPpldTWbM+9ZmpXArhCQmZdPHeuavI3q4xDUAQ9y8wCCKhTDMFsWNVvpWuztUKref64CoJdbydybfI2+Of85mffZ9rriCoAWtiQHgtPH0gTVASQR/oEKE4CuZN9gje0VQLAABJVObMNiGoByI5c6AHNeX8euZIYRft1PO7ZgucuIiybohXEJQCHrAMKEMk4rJNdx9UdWhoccdyDKAOdjcONgbrM9IP0zR5ptvOzlsDqAoEJWvvNBohtUCWzmEdz2ISniiLZ4AAXA/I6r/aDaaUEhoLiVwC10fAHYRebB3GNsNwAVBtqEGuRsM4UVAN0LVpNLCMglzPkKgOuljOoJbJZMXdvr+qiwegBTAHOpZM1HAHYEpLveGZfBj9NKyZ4vtADYYbe4HoAm6bq8OJXAIgAFwBUCAvdNN+OT+YSAXAOAlQtxK4GDDJseq18bqSVkfzS+vQQJwG4y9zcoBOS6L/kKQJiYBB3TvmY2WgDC6gHM88/FA4hryIK2CROAVjID8wUdPyz8EsfLjjPvejbzDQFp0hQAW0S19yEhoAIQFALKxQPIpQ6gI3kAZvt2/TDa10inD/GnWgBWUNjvmQaFgGyjHzRfKA/AvsemAQzqCRwlAFtQL32UALg8gLjGLYo4AmC/R3E9gqD8tscb0O9ei5GvQgpA0s25gwqeICGggpJvCMh+UHWrgrCOYC3W/soJ1wOvzzWsNKvnbQ9gBaopYtzPHYbRA9UO3eUB2G3/XfMuo51v6creV5DQBMW6g17qt4kOAQV5AGEdrQopAPY7o/dttrjJpRVQIcJBceoUXAJgXzMc6yRJmN0JCxcWgooTAFcIyCUAQYYuyFV1hYA6kgdglkSCSrN63uUBABxagLzpFjBBAhDHGzDvS3s8NVvkzX0FeSBRHgCENwXtiuplq88/LMZeiDqAuAJgrufyEKOWC1EhHLQPuxI4Fw/AHEcqKeK0PpQQUAGIGwJylW5cpcxK8gBcQxwEldoG+8vN/vJKf5qUALgEKcgDsOsA2iPUtniYy7ZQxg0BgWoJFCQA9jhIUSX+fGLZ7fEAzLSoEFDQ82OWfAvtAdgl/qhWQEmX/s1jQfY1s5+bJKgoAQgKAdlpu63lOB5AR2oG6qooDRrjxiztmaWUD435jSgxKIQA2J3AwG1Egkr9hfYA4oSAwuoDXLyN6tnqGvvWHgZDf5QFkmkGmmsdgJkWlZ+gZ6nQHkB76gDS6M0f1ytKgooTgDghoFZrOciwuFocaNpjWIqNS7xc52qXZl29OjWriP+1qzBsA0hAfoJCQGGl9lxLe2H7yrcSGMJbAtnDYOjj6v2lJQBhHsAeIy1fD6BUQkDFEACXoEsIqADEDQHZAhBVsnAZzHJuBuoKXwU1/bQNgMs7AvWxk7hfuwpjAMrAbDHSgox+VIWw3jbfl10b/D3WsuuYQaLpQncGcwnA/v7UJYClUgdQZaQFGdsW1HVziXQuArAHd8sfc16P5WWn23nSy+Z5pR0CEg8gIar8XxwBsKdRISCXsS9nD8CV9zitgPT/5vqat4BhtH/0wYGo8JJ5vaNK/a55V6ugfASgxdguTsVvnJdaC4BLMIf6+TU/nhrkhRWrDqDKSAszbub2ZhPaXFoBBYWOwlrxlbIHYNcBiAAUCD0YWS4hoCBXzA4ZdDQPIG4dQK4eQDVwQDvzZncCM4+ZSx2A2Xa8PQIQtK8gryOOB7AD1YN6pOO/A1DG3/Zi9P7SCgHZ75HLA4gK+UD2uxZWyILosE+cVkVmOM7+z84PlE4dgISA2on+TFycSuC4ISBd+oiqAyg3TyDMA4iKZ4cJALS/HsBsA69xvdxBfQL0ue20liE5AQirNwliFXCwI/0A1DcD7Hzo/dnPtW3s4hBHAFzH1mgvzxUCsgtPLg/ADt+4RlKNivvHmdf5iHteSSEhoBTIxwOIU7LQHYlsg2kag7ijMJYKLg8gTiWw3tZcX6MFoL31AGYvWE2uIaBCC4C5r6jjx32pCyUA5nLc8eTzEQBzPW1Uwuok4gpAVDgoaQFIwwMwS/em4HX4ZqD9+vXjD3/4AytWrGD58uWMHTs2sWNpAShkJbB+sV0G09VaqFywPQDTsOUbAvrATyuEANgeQNx+APq/FtwCkOt9sgUgLOyTSwgI4E3U2Pv7GmmdUHUAtgAEdbxyeaZxaK8AaHKpA9hD9PuWlAC4PPQ0BSAsTJZ0CKioXwS79957mTNnDpdccgldunShZ8+eiR0rLASUiwC4Snb2cL/d6VgeQJAA7CJTqowSAA/VvLE9AtAbNUZ7WAgoSqihbdhmOzDV3+9Y1LnE+YBNC8oQucSkPT2BQXkAoLyA1/z5/fx8BXkAcUu3UbQ3BGRuG2bczO2DPIAgAYjySMMKKqUWAjI9s4oJAfXt25eTTz6Z6dOnA7B79262bUvu0wuFDAHZJTtXab/QHoBuxmbnrdX6vxDYHkCQMcvFA4D2NwV1dQIzjxlVCWxeM/uefxv18Roc/wXRAlwF3Ggshz0nej5uCAjgECNtqD8NCwGZ980j+hxcmPtwDfHgOnauHoD9vOTiAQSN+pqPBxDUWCNND8AkqLDQ4SqBR4wYwZYtW3jooYdYtGgR06ZNc3oAEydOpKGhgYaGBmprXX0j4xEWAsq3EljfLPMFd1UI5iIAdiXZDmu60/p/p/G/LuXqhyVfUdCGzIzrxyll6XXN/Jq8RfTnDsNwdQLT+bXz4wrH6Lw9BTxt5dfcj32Nd1jLZk/xJahwTdAx9XyuHsBalME7wkjTA8TFrQPAsRwHs0SatAdgvmtBBS5bANpj9O1WQOY5uNLSFgDz2B3aA6iurmb06NFMnTqV0aNH8+mnnzJ58uQ2602bNo26ujrq6urYunVr3scLCwEFlarDHsgWMiWsIA/AFoCg1kBmZ5YgA28v21OdxxayRUHnORd03l0d3aIEIEz03kJ9UHyg4784uMYBIiA/YSGg24B7rG3N+aBrbE9dz4spGlEGKEwA9qDE5Wgj7cv+tqusdYM8APO/fGlvHUBQk0v9TEY1A01CAOyCUbFDQDa5eovtoWgCsH79etavX8+CBQsAeOKJJxg9enRixwsLAWGl7bGWo+LJLmPfgvoc4kNkYrhBnWd24DboYcuu9VvJDm8EeRFRzVK1kOQyBLQ+lm4DHiQAkH8YKCoEFNcDMLdxFQTiCMAeMiVlc18fARcBM8l+kXOtBAZYTLYAHA6soa2xDdtfEgLg8ixdxzYLW7q+yM6rNkC5hIDyMfpmRblNmC1IKvQShkvQO1wIaNOmTaxbt46DD1aN3U477TSWL1+e2PHCQkBYaXFCQKaQ6Juzm+zvC3+CihF/6KfZJXPToIQZdle6a2p7AFHToIfK5QG4SrAuY6Y/Gp6UALSQPdAcuO+TXQewHff3bfP1AFzbmSGmbWSu36cBeYwq1S1GDf2sO88dDixzrJe2AJj7rHasZ29rekZBAmAKdNIegE2YLWjv9cuHkgoBLVy4kG9/+9vU1NQU/ODf/e53eeyxx2hqauLoo4/mZz/7WcGPoQkLAWnMUr05dYWAzDiwnr8KeMDal3ksl+Hf4+8zF0MfNLVL7vkKgd5PkACEhYC0ALgMwjuoa5qvAAxAfV84yIU3S0y2GNwKXGxs45Fd6jT3E0eEXdvZz9R84ELg74RfsyAW+9PRqJZlXwSWOtZLUgDMfbrOU3t8LgNlvmv2e6fX19vbHoBLDHY60pISALvRRZqkKQCRzUAvvfRSvv71r9PQ0MDChQt56KGHmDt3bkEO3tTURF1dXUH2FUUuISB76orhmjFMPf8ocIJj/2ElS21stZGNa7SDjJKXwz52An38aRc/D138/fwZJZpHElyh+TnqC11mfvQD5fIAdgPrCf/aVRgDaRv+gWCjb+b5Y9x1B4XwAGyP0eRpa51cBeBTYBzwLspYpu0B2P1B7H1WOdI0YQJghwzj1AFoYcjV6Lv6H5i48h52XkkT5NEmQaQH8NZbb/Hv//7vHHzwwcyYMYMHH3yQd999l1tvvZX+/fsnlK3CEycEFNTUMqwOYA2w2tiH64bFEYBcwzf21Kyc3hWxbpSHsBv438DPjfyHvZAQLwQEqnVLoQUgTgjIhWl09DLEq5A3t9PPTdhLmk+p7nNgLnAe8N/848xzrJdrfDtf9L5MUahypGnihIBcAhDkces6hDQ8gOqQ/5Km5CqBjzjiCO666y7uvPNOnnzySS655BL+8Y9/8OKLLyaUrcJjh4BcFVn2wxz1QIJ6OX9g7MMMDWHNuwxvIQRAN/00vYndOezDzpdtOHOpBE5SAAagehTbRL30QYY5Xw/A1dwyavA/81rH9QAAnkG1//8R8DywwbFOC23DWeZ/hcLlAYQZykJ6AKbnHlQPFVbqD7vmdsjXzlfa6PtpeppFCwEtXLiQ5uZmpk+fzuTJk9m1S2VlwYIFnHDCCRFblw52CMhFkACEPZA2YR5AIQQgKPSjfx7B+wrqU2Cn2yKWTx1AmAAMJvvrbHHJ1QOYhYqdBx0nVwH43JjaBs/el82TqGvyAeHGyOZp4CZUh7DfBKxjGljXf+a0Pbj2FWYo7VZA5rZ62awEzkUAkvAA4gpb0rQAXwP+RuYToEUbCuKSSy5h7dq1WWnDhw/nnXfe4aKLLkooW4XHDgG5sB/m+cBsVPzVLHHcT+bG2LgepjghIP0C5GL4dXpcAYgq+ZtNWM3pblSF8EKgCfeLFacOADJj3Q+jbXv2MPqjvDg7jm/m0+4JvBR3pam5nXmf1qPO8XXgXwi+X67SvukVutgO/N7Kb5xS3T+Aw4CjgMaAdcIEIKx+Ilf0PkxjH2YozdBYlAcQ1Qw0rgBEtSQKE4C455UGM/3pPv60aCGgJ554IlZaqaNDQLl4AG8CZ5PtirUCL5F5mW3CPIA4dQD5tAbS4pGrN+HyCFrJtG/XLWV2+9M64C8Et46CzHWOEoBcw0CuTyFqgjyAKGyj/QnqHLWhjbpfJnZ9QtRxIb4HtIdg46/3F+WRFiKU4RKTOJWlYSGgV/3pcwQb7EJ5AHtwXwfXNUo7BPQd4HJH+mqUrXnV8V8hCPQADjnkEL785S/Tr18/Lrjggr3pffv2pXv37gllJznieAD6Zm93/PdMzOO4PAC7g9EOMs0/baOtW6/EDQW1xwOIat0C2UNLaHQ7/C1kDLN9XQstAAP9aZgHkGul2Qu4K1X19dB9OkxRDhKAu4j/kurtCzV+U1ohIHufkDEgYYbSzJ9+vvW1nU8mTKfHPUpKAKKuUTE9gP8MSN8JXJbgcUMF4Nxzz6WmpoavfvWre9O3b9/OxIkTE8xSMnQjuKJMUw/8mMwwASbz/V8UrhfuDZSSv+svu0r+dsn9Q5QQzQOOBR5GNdm8209/GPXVqNdQoYvtqO/FHowykjtRJVp9vDhTs4LSPB9bAN5Cfa1qDfAlPy2uAHzgHy9fD8AlAO+hSshNwBdQ93lrjH3+a0D6q6gY7GrgVGAByhPciOrg5RKAn8Q4nmYn2SNbtpcVQD9j+TQy30wupAfgKu270uxB/2wP4FwyA+9BW+/A1ZqrEAJgFgr+F+q9MXF5AMUKAaVFoADMmjWLWbNmMXbsWObNc5WTyouuRJcK96BaW7QHVwhiMcow3+Ava0Orfx/76zegYtaPotp7/9j/79f+dq/40+uM/QLMMY7V3T+PsSiBqPH//++oYQr08cEdCnJ1CnOFU9YY/0N8AfBQQpivB+AKAf0D1VlKM4K2A6blwh5ghj8/EjUO/4OoZ+g3wCAygpQP96O8j0LxY2vZbJtnD1fRHvS+thhpdiECYBTQ11h+iezWS+bzamI+S/q5M5t+6v/MAtRnRAvA57QVgHuMeZ1uWjndmKEYrYDSJFAAfvCDH3DnnXdyxRVXcPnlbaNT1157baIZKzSuViffxt2xpj1sRxm/zY7/1vrpq1Hfdf09qnT5KOpBdxm3XNEv4l/96aX+dA3qJaxDVXJeSaYUagpCHA/AJKgNetgIqPk0BR2IelE/jrFue4y/Cw91PjtQHsDq8NUjWU/b0mdS5BvLPoe293QVcC3Z9V/fRT1bzxlp9rAbcS3FCtQ3Izaj6t/e8NMfJvNhnO+Q6Q1+PupZ3gLcghKWgcBKVK/znWSHWoMKgNuBMYA5EM184JuENyLoCAQKwIoVKwDVDLQj4BKAqQkcZzvK/XUZ8z8AT6BeynvJhGjSQN/Fsajeu62okvMVKKOmRyS1jX1U+/YN/na24IUJwDsoIcqFARRGICuNTcCzwB05bveXgPT7rOWPUMa3EPydTOjoATLDqjxhrGN6N2Ye/48/bQYO9ecfRonW56jwnSt8qGmwlh9Gedxr267aoQgUgD/96U8APPLII6llJknihIAKhauzkka7tGkaf5sdwC9RN/9VVJx7De7Ytu56H8SLqFJXs5UeVuJciyrR9cFd4e5iIOEvsOBmD6qzYiWyGfijP/9DVHg0Fzq68YcYzUDnzp1Lv36ZKqaamhrmzAmK4pUuaQpAudCCcrl/g2qB0YAqhZl8D/hFxH6ajfk3Yxw3n5ZAAxABEPJnB/HCh5VGpAB84QtfyPpUY3NzM/vtF9QNqnSppjhje5cT96FCQiZPEN4G3eYrqGGLw8hHAIJ6AQuCkD+RAtDa2srQoUP3Lh9wwAF4nheyRWmiR7kUkuVjMpV3QeQqAJ1QPa/FAxCEwhI5FMTNN9/M3//+d1555RU6derESSedxKRJk9LIW0ERD6B00H0c4grAvqj7Jx6AIBSWSAF47rnnGD16NGPHjgXguuuu48MP7W8ylT7ViAdQSuTSFDSsF7AgCPkTKQAAxx9/PCeffPLe5T//+c8Fy0Dnzp1ZuHAhGzZsyOpxXGhEAEqLtcT/MpgIgCAkQ2QdwG233ca1117L8uXLWb58Oddeey0//elPC5aBa6+9dm+fgySROoDSIhcPIGwgOEEQ2ocX9mtqavI6deq0d7lz585eU1NT6DZxf4MHD/aef/5575//+Z+9Z599NnL9hoaGvI/1MngvFiDP8ivM7xrwPPBqY6x7vb9unxLIt/zkV46/INsZ64tg5gfhzT4B7eWee+7hhhtuYM+e4HERJ06cSENDAw0NDdTW1uZ9LAkBlRZr/WkcL2AAqh133E5jgiDEI7IO4LbbbqOxsZGXXnqJTp06cfLJJzN58uR2H/icc85h8+bNLFq0iFNOOSVwvWnTpjFt2jQAGhrsDtvxEQEoLUwBiLqr0gtYEJIhUgBmzpzJyy+/TF2dGr3lxhtvZNOm9kdjTzjhBM477zzOPvtsunfvTt++ffnd737Hv/5r0CC97UPqAEqLXDyAQYgACEISBArAqFGjspbXr1fjFw4aNIhBgwbR2NjYrgNPmTKFKVOmAHDKKafw/e9/PzHjD+IBlBqfokZxjCMAQ8kMfS0IQuEIFIC77rorcCPP8zjttNMSyVBSSEew0mMt8QXg2YTzIgiVSKAAnHrqqall4pVXXuGVV16JXrEdiAdQeqwl+0MuLvZBDV+9LvnsCELFEdkKqEePHtx88838+tfqu1Rf/OIXOeeccxLPWKGROoDSYy0wjPCHUI9CJQIgCIUnUgAeeughdu3axfHHHw/Ahg0b+MlPcvkCamkgHkDpsRY1TPcgVCn/3xzriAAIQnJECsBBBx3EnXfeye7dKoK+Y8cOOnXqlHjGCo3UAZQeZkugX6C+S3CitY4IgCAkR6QA7Nq1i+7du+8dAvrAAw/k88/tjyuWPuIBlB76w/IHk6kL2GmtMxT1IR8ZBkIQCk+gANx///2ccMIJ3HrrrcyZM4ehQ4fy6KOP8sILL3DDDTekmceCIAJQeryD+jD9YcBgP8320oahvjvspZctQagYAlsBrVq1ijvvvJP999+f+vp6nn/+eRYtWsS1115blsNBSyVw6eEBK4Avoz74AlBlrXOov44gCIUn0AO47777OP744znllFNYs2YNF154IXfddRff/va3GTlyZJp5LAhSB1CaLEcJgKbKmj+U6C+MCYKQH5F1AO+99x533HEHo0eP5vLLL+eCCy5IZfjmQiMhoNLkDWCIsWwKwEFAd2BZqjkShMohUgCqqqo499xzefTRR5k9ezZvvvkmF154YRp5KygiAKXJcmvZFADtGYgHIAjJEFgHMG7cOC6//HLOPvtsFixYwMyZM5k0aRKfffZZmvkrCPokRQBKj5etZVMADgf2IHUAgpAUgQJw0003MWPGDK6//nqam5tTzFLh0ScpdQClx3bgNuAmf1m7pJ2AfwGaUC2FBEEoPIECUG6DvYUhHkBpMwU13PO9KA/gJOAOlAdweRHzJQgdnVhfBCt3RABKH/1RmCpgPDAW+BPweNFyJAgdn8gPwnQEuvhTEYDSpdWfVgH9UT1/v1q87AhCRSAegFASmAJQAzQXLSeCUDlUlABIJXDpYnsAHxcxL4JQKRRNAIYMGcKLL77IG2+8wbJly7jmmmsSO5Z4AKWPFoDOiAcgCGlRtDqAlpYWrr/+ehobG+nduzevv/469fX1ifQyljqA0mePP9UewNtFzIsgVApF8wA2bty498Pyn3zyCStWrGDw4MERW+WHeAClj9QBCEL6lEQroGHDhjFq1Cjmz5/f5r+JEycyadIkAGpra/Pav9QBlD52HUBz8bIiCBVD0SuBe/XqxZNPPsl1113H9u3b2/w/bdo06urqqKurY+vWrXkdQzyA0kcLQF9UyE4qgQUheYoqANXV1Tz55JM89thjPP3008kdx5+KAJQuWgD29afNRcqHIFQSRRWA6dOns2LFCu6+++5EjyOVwKWPFgAd5BMPQBCSp2gCcMIJJ3DllVdy6qmn0tjYSGNjI+PHj0/kWFIHUProVkD7+NPmIuVDECqJolUCv/rqq3Tq1CmVY0kIqPSREJAgpE/RK4HTQASg9JEQkCCkT0UIgNQBlD62B7CtWBkRhAqiIgRAPIDSRwtAT3+6s1gZEYQKoqIEQCqBSxctAN38qYi1ICRPRQmAGJXSRbcC6upP5V4JQvJUhABIHUDpY3sArUErCoJQMCpCAMQDKH20we/qz3tFzIsgVAoVJQBSB1C6mCV+EWpBSIeKEgAxLKWNrgeQ+yQI6SACIJQM2guQ+yQI6VARAiCVwOWBeACCkC4VIQBSB1AeiAcgCOlSUQIghqW0EQEQhHSpKAGQtuWljQiAIKRLRQhAF6RteTkgAiAI6VIRAlCNxP/LAREAQUiXogrAmWeeycqVK1m9ejU33nhjYsepRoxKOSCtgAQhXYomAJ07d+aXv/wl48eP57DDDuPyyy/n0EMPTeRYIgDlgXgAgpAuRROAMWPGsGbNGtauXcvu3buZOXMm559/fiLH6oIYlXJABEAQ0qVo3wQePHgw69at27u8fv16jjvuuDbrTZw4kUmTJgFQW1vb5v84PAO8mdeWQpqIAAhCupR8JfC0adOoq6ujrq6OrVu35rWPeuAXhc2WkAAiAIKQLkUTgA0bNjB06NC9y0OGDGHDhg3Fyo5QAogACEK6FE0AGhoaGDlyJMOHD6dLly5cdtllzJo1q1jZEUoAaQUkCOlStDqA1tZWrr76ap577jmqqqp48MEHWb58ebGyI5QA4gEIQroUTQAAZs+ezezZs4uZBaGEEAEQhHQp+UpgoXIQARCEdBEBEEoGEQBBSBcRAKFkEAEQhHQRARBKBmkFJAjpIgIglAziAQhCuogACCWDCIAgpIsIgFAyiAAIQrqIAAglgwiAIKSLCIBQMogACEK6iAAIJYO0AhKEdBEBEEoG8QAEIV1EAISSQQRAENJFBEAoGVqtqSAIySICIJQM4gEIQrqIAAglgwiAIKRLUQTgjjvuYMWKFTQ1NfHUU0/Rr1+/YmRDKDGkFZAgpEtRBKC+vp7DDz+co446ilWrVnHTTTcVIxtCiSEegCCkS9EEoLVVve7z5s1jyJAhxciGUGKIAAhCuhS9DuCqq66Sz0IKgAiAIKRNYt8Erq+vZ+DAgW3Sb775ZmbNmgXAlClTaGlp4bHHHgvcz8SJE5k0aRIAtbW1yWRWKAlEAAQhfbxi/CZMmOD913/9l9ejR4/Y2zQ0NBQlr/JL53c/eB54Xy+BvMhPfh3pF2Q7E/MAwjjzzDO54YYbOOWUU9ixY0cxsiCUIOIBCEK6FKUO4P7776dPnz7U19fT2NjI1KlTi5ENocSQZqCCkC5F8QBGjhxZjMMKJY54AIKQLkVvBSQIGhEAQUgXEQChZBABEIR0EQEQSgYRAEFIFxEAoWQQARCEdBEBEEoGaQUkCOkiAiCUDOIBCEK6iAAIJYMIgCCkiwiAUDKIAAhCuogACCWDCIAgpIsIgFAyiAAIQrqIAAglg7QCEoR0EQEQSgbxAAQhXUQAhJJBBEAQ0kUEQCgZtOFvDV1LEIRCIQIglAx/Af4PsK7YGRGECqEo3wMQBBcfALcUOxOCUEEU1QP43ve+h+d57LvvvsXMhiAIQkVSNAEYMmQIZ5xxBu+++26xsiAIglDRFE0A7r77bm644QY8zytWFgRBECqaotQBnHfeeWzYsIElS5ZErjtx4kQmTZoEQG1tbdJZEwRBqBgSE4D6+noGDhzYJv3mm29mypQpnHHGGbH2M23aNKZNmwZAQ0NDQfMoCIJQySQmAKeffroz/fDDD2fEiBE0NTUBqi5g0aJFjBkzhk2bNiWVHUEQBMEi9RDQsmXLGDBgwN7ltWvXcuyxx/Lhhx+mnRVBEISKRjqCCYIgVCidgLJphrN58+a8m43W1taydevWAucoPco5/5L34lHO+S/nvENp5X/YsGHst99+zv+8Svg1NDQUPQ+Vmn/Ju+S/0vJeLvmXEJAgCEKFIgIgCIJQoVSMADzwwAPFzkK7KOf8S96LRznnv5zzDuWR/7KqBBYEQRAKR8V4AIIgCEI2IgCCIAgVSkUIwJlnnsnKlStZvXo1N954Y7GzE8natWtZsmQJjY2Ne8c/6t+/P3PnzmXVqlXMnTuXmpqa4mbSYPr06WzatImlS5fuTQvL77333svq1atpampi1KhRRchxBlfeb7nlFtavX09jYyONjY2MHz9+73+TJ09m9erVrFy5MvZ4VkkxZMgQXnzxRd544w2WLVvGNddcA5THtQ/Ke7lc+27dujF//nwWL17MsmXLuPXWWwEYPnw48+bNY/Xq1cycOZMuXboA0LVrV2bOnMnq1auZN28ew4YNK2Lusyl6W9Qkf507d/bWrFnjjRgxwuvSpYu3ePFi79BDDy16vsJ+a9eu9fbdd9+stJ///OfejTfe6AHejTfe6N1+++1Fz6f+nXTSSd6oUaO8pUuXRuZ3/Pjx3l/+8hcP8I477jhv3rx5JZf3W265xbv++uvbrHvooYd6ixcv9rp27eoNHz7cW7Nmjde5c+ei5X3gwIHeqFGjPMDr3bu39+abb3qHHnpoWVz7oLyXy7UHvF69enmAV11d7c2bN8877rjjvN///vfepZde6gHe1KlTvW9+85se4H3rW9/ypk6d6gHepZde6s2cObOoeTd+Rc9Aor+xY8d6c+bM2bs8efJkb/LkyUXPV9jPJQArV670Bg4c6IF6eVauXFn0fJq/YcOGZRnRoPz+6le/8i677DLneqWS9yAjZD87c+bM8caOHVv0a69/f/zjH71x48aV1bW3816O175Hjx7e66+/7o0ZM8bbsmWLV1VV5UG27THzW1VV5W3ZsqXo+YYK6Ag2ePBg1q3LfGZ8/fr1DB48uIg5isbzPObOncvChQuZOHEiAAMGDGDjxo0AbNy4MWtAvVIkKL/lcj+uvvpqmpqamD59+t4QSinnfdiwYYwaNYr58+eX3bU38w7lc+07d+5MY2Mjmzdvpr6+nrfeeovm5mZaW1vb5NHMf2trK9u2bSuJT+F2eAEoR0488USOOeYYxo8fz3e+8x1OOumkNuuU25fUyim/U6dO5aCDDuLoo4/mgw8+4K677ip2lkLp1asXTz75JNdddx3bt29v838pX3s77+V07ffs2cOoUaMYMmQIY8aM4Utf+lKxs5QzHV4ANmzYwNChQ/cuDxkyhA0bNhQxR9G8//77AGzZsoWnn35677cS9Ad2Bg4cyObNm4uZxUiC8lsO92Pz5s3s2bMHz/OYNm0aY8aMAUoz79XV1Tz55JM89thjPP3000D5XHtX3svp2mu2bdvGSy+9xFe+8hVqamqoqqoCsvNo5r+qqop+/fqVxBD4HV4AGhoaGDlyJMOHD6dLly5cdtllzJo1q9jZCqRnz5707t177/wZZ5zBsmXLmDVrFhMmTABgwoQJPPPMM8XMZiRB+Z01axZXXnklAMcddxzbtm3bG64oFcwv2V1wwQUsW7YMUHm/7LLL6Nq1K8OHD2fkyJEsWLCgWNkEVCumFStWcPfdd+9NK5dr78p7uVz72tpa+vXrB0D37t05/fTTWbFiBS+99BIXX3wx0Pba63ty8cUX8+KLLxYn4w6KXhGR9G/8+PHem2++6a1Zs8abMmVK0fMT9hsxYoS3ePFib/Hixd6yZcv25nefffbxnn/+eW/VqlVefX29179//6LnVf9mzJjhvf/++96uXbu8devWeVdddVVofu+//35vzZo13pIlS7xjjjmm5PL+yCOPeEuWLPGampq8Z555JquidMqUKd6aNWu8lStXemeddVZR837CCSd4nud5TU1NXmNjo9fY2OiNHz++LK59UN7L5dofccQR3qJFi7ympiZv6dKl3g9/+EMP1Ps7f/58b/Xq1d7jjz/ude3a1QO8bt26eY8//ri3evVqb/78+d6IESOKmn/9k6EgBEEQKpQOHwISBEEQ3IgACIIgVCgiAIIgCBWKCIAgCEKFIgIgCIJQoYgACIIgVCgiAEJFss8+++wdcviDDz7YOwTx9u3b+eUvf1nw4z300EO8/fbbfOMb3whc58QTT+SNN97IGppaEJKm6J0R5Ce/Yv6CRqAs5O+hhx7yLrroosj17JFJ5Se/JH/iAQiCwSmnnMKzzz4LqI+TPPzww/z1r3/lnXfe4YILLuDnP/85S5YsYfbs2VRXVwMwevRoXn75ZRYuXMicOXOyhjMI4uKLL2bp0qUsXryYV155JdFzEoQgRAAEIYSDDjqIU089lfPOO49HH32Ul156iSOPPJIdO3ZwzjnnUF1dzS9+8Qsuvvhijj32WB588EF++tOfRu73Rz/6EWeeeSZHH3005513XgpnIghtqS52BgShlJk9ezYtLS0sXbqUqqoq5syZA8DSpUsZPnw4hxxyCIcffjj19fWAGunxgw8+iNzvq6++ysMPP8zjjz/OU089leg5CEIQIgCCEMLnn38OgOd57N69e2/6nj17qK6uplOnTrzxxhscf/zxOe33W9/6FmPGjOGcc87h9ddf55hjjuGjjz4qaN4FIQoJAQlCO3jzzTf5whe+wNixYwE1xv1hhx0Wud2BBx7IggULuOWWW9iyZUvWWPeCkBbiAQhCO9i9ezcXX3wx9913H/369aO6upp77rmH5cuXh2535513MnLkSDp16sQLL7xAU1NTSjkWhGyK3hRJfvLr6D9pBiq/UvxJCEgQUmDbtm38+Mc/juwI9uyzz7J169YUcyZUMvJBGEEQhApFPABBEIQKRQRAEAShQhEBEARBqFBEAARBECqU/w8MDfIA89x2wgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import cubic_spline_planner\n",
    "ax = [0,3,6,13,25,30,40,54,90,92,100]\n",
    "ay = [0,3,6,75,24,30,38,50,90,90,100]\n",
    "cx, cy, cyaw, ck, s = cubic_spline_planner.calc_spline_course(ax, ay, ds=1)\n",
    "waypoints = []\n",
    "for i in range(len(cx)):\n",
    "    waypoints.append([cx[i],cy[i],cyaw[i] ])\n",
    "    \n",
    "R = np.array([[0.01,   0],[  0, 0.01]])\n",
    "trajectory,controls,waypoints_reached,error = get_control_waypoints(waypoints,R,dt=0.1,error_th = 2, verbose=True)\n",
    "get_animation(waypoints,trajectory, marker_txt =False)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
